Collections of linked databases

ABSTRACT

This invention is generally directed to one or more methods or systems relating to inferential networks. This invention is further directed to methods and systems for making and using inferential networks. Still further, this invention is generally directed to making one or more inferential networks by using data generated from directed searches of collections of linked databases.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a continuation of International Application No.PCT/US2005/006617, filed on Mar. 2, 2005, now published asWO/2006/036187, which 1) is a continuation-in-part of InternationalApplication No. PCT/US2005/005847, filed on Feb. 24, 2005, now publishedas WO/2006/036186, 2) claims the benefit of U.S. Provisional ApplicationNo. 60/652,661, filed on Feb. 14, 2005, 3) is a continuation-in-part ofInternational Application No. PCT/US2004/038064, filed on Nov. 15, 2004,now published as WO/2006/036165, and 4) is a continuation-in-part ofInternational Application No. PCT/US2004/030259, filed on Sep. 15, 2004,now published as WO/2006/041425. These five prior applications arehereby incorporated into the present application by reference.

FIELD OF THE INVENTION

This invention is generally directed to making and using inferentialnetworks. The invention is further directed to making inferentialnetworks using data generated from directed searches of collections oflinked databases.

BACKGROUND OF THE INVENTION

When seeking information, many people rely upon sources such as theinternet, intranets, pamphlets, magazines, and advertisements to providethem with adequate information and ultimately to aid in theirdecision-making process. In their searches, however, such sources ofteninclude barriers that prevent people from acquiring the valid, reliableand useful information they need. Notably, the anonymity ofinterconnected computer networks (e.g., the internet) prevents peoplefrom trusting the reliability of the information source. Clearly, mostpeople would rather consult their friends and colleagues that they knowand trust on a first name basis—or knowledgeable people that they knowthrough their friends and colleagues—when seeking the answer to aparticular question. For example, it is well known that informalcommunication via personal communication networks allows decision makersto reduce the uncertainty regarding unfamiliar technologies and/orproducts by questioning and consulting trusted others. Posing questionsto the members of one's personal communication network allowsindividuals to obtain first, second, and third-hand accounts fromindividuals they know directly or through intermediaries. Theoretically,the varied experiences of one's network of peers, acquaintances, andpeople connected to the person through countless others should more thanadequately serve to answer one's questions. Unfortunately, experientialand other knowledge can be difficult to procure; because people areunaware of who in their interpersonal network has experience orinformation regarding the information they seek, informal searches foradvice can seem arbitrary, unfocused, and inefficient. The absence of aformal map or knowledge of communication structure prevents the personfrom realizing the full potential of the collective IQ of his network offriends and colleagues.

Social network analysis is known and has been described as the mappingand measuring of relationships and flows between people, groups,organizations, computers, or other information/knowledge processingentities.

Social network analysis (SNA) can be used to generate data and drawconclusions based upon the flow of information (or other resources)within a social network. SNA maps the relationships of people within asocial network in order to monitor, understand, and utilize theinformational flow within the network—who do people get theirinformation from and who do they give it to? A social network isdistinct from an organizational chart because the organizational chartshows formal relationships—who works where and who reports to whom. Onthe other hand, a social-network-analysis map shows more informalrelationships—who knows who and who do they share information with. SNAtherefore facilitates visualizing and understanding personalrelationships that can either facilitate or impede knowledge creationand sharing.

While social network analysis is known, little has been done tostreamline its use in an effort to maximize its potential. Further,implementations of social-network analysis have yet to be fullyexplored. Specifically, most individuals interested in social networkdata have merely conducted interviews or surveys to obtain the data, andthey have then kept the conclusions drawn from such data exclusively inthe world of academia. For example, sociologists who studied thediffusion of hybrid seeds through the social networks of farmers in Iowapublished their findings in academic journals. They did not, however,disclose the conclusions that they reached based on the analysis oftheir data to the general public.

SNA is gaining popularity in the field of marketing in order tofacilitate the diffusion of innovations (e.g., new products) throughcustomer networks. To this end, a number of companies have conductedpreliminary data analyses using SNA in an attempt to map customernetworks and determine who most customers contact for advice within aparticular domain. In theory, if a company can identify and market tothe small percentage of people that make up the opinion leadership oropinion leaders within a given customer network, they can lower both thecost of marketing and the time it takes for the innovation to diffusethrough the customer network. Marketing departments are thereforeanxious to identify “opinion leaders” within a given field. Suchindividuals are often highly connected “hubs” within a social networkweb, and they are important targets for marketing because other membersin the customer network often go to them for advice regarding the latesttrends and innovations. Clearly, the ability to selectively targetopinion leaders, which may cut advertising and marketing costs whilesimultaneously increasing the effectiveness of marketing messages, wouldbe highly beneficial. However, with current technology, collecting,mapping, and identifying what role each potential customer plays withina given network demands considerable time, effort, and money-making suchan approach prohibitive to all but a few companies.

While companies first demonstrated interest in the utility of SNA fortargeted marketing in the 1950's, prior-art technology is slow andcumbersome. Most recently in the pharmaceutical domain, somepharmaceutical companies gathered relational information within themedical field by sending a two-page survey to approximately 800,000physicians in the United States. The pharmaceutical companies paid eachparticipating physician approximately $250 for their time, but thesurvey yielded only a 5% to 8% response rate—this equates to a one time$10,000,000 to $16,000,000 data-collection procedure. Furtherlimitations on the accuracy or utility of such a strategy include the“static” nature of a one-time survey that fails to capture the dynamicnature of social networks.

Additional prior-art methods for performing SNA exist. One prior artmethod attempts to draw an inference on who is well known andinfluential within the field of medicine based on general publications,conference presentations and disclosures. This prior-art method isclearly limited in its lack of a social-network map that clearly depictsthe informal and formal communication links between physicians. In otherwords, the approach is lacking because the data does not directly andclearly correspond to advice, influence, or communication amongphysicians. Clearly, a new approach to the collection of reliable,valid, meaningful, and cost-effective social-network data is needed.

In the domains of leisure and entertainment, parlor games such as “SixDegrees of Kevin Bacon” and websites such as “Friendster” and “LinkedIn”have demonstrated the ability of an internet system to create socialnetworks of friends and business associates for the purposes of makingfriends, finding dates, identifying potential job candidates, andseeking employment. A major drawback of such popular social-networksites, however, is the seemingly arbitrariness of the links betweenusers. Allowing “friends” to link to one another in a situation thatalmost promotes competition to score high volumes of links creates achaotic environment wherein the context, strength, or value ofrelationships between users cannot be ascertained. Arbitrary linksundermine the utility of social networks that purport to connect peopleto trustworthy second and third-degree contacts premised upon mutual“friends.” Therefore, the data captured and utilized by these websitesis highly unreliable. Because the websites have not set parameters,guidelines, or norms to govern or define the links between users, thesocial networks generated by these sites provide limited aid to usersand are nearly useless to parties interested in using social-networkdata for their own purposes.

Prior-art methods for inviting new people into social networks online orindicating first-degree contacts via a survey typically lack thesophistication to accurately capture the directionality of anestablished social-network link. It is generally known thatsocial-network links can be either unidirectional (e.g., from A to B) orbi-directional (e.g., from A to B and from B to A). Capturing reliable,valid, and meaningful social-network data typically necessitates thedirectionality of the links within a social-network. Establishing andrecording accurate directionality information about social-network linksincreases both the meaning and utility of a social-network map andsocial-network data generated therefrom. Prior-art methods for inviting(or listing) people into a social network often erroneously orprematurely infer bi-directional relationships—and misinterpretation ofthe directionality of a link leads to misleading information.

More specifically, prior-art methods directed to determining thedirectionality of social-network links do not provide a way to confirmthe actual existence of a unidirectional or bi-directional link. Forexample, in the prior art, a first person will typically declare that asecond person is linked to the first person, and as a result, the secondperson is incorporated into the first person's social network as aunidirectional or bi-directional link. Note that the prior-art methodsdon't provide for a way to confirm the existence or directionality ofthe link. In other words, the prior art doesn't provide for a method bywhich the second person can confirm or deny the relationship that thefirst person has alleged. Further, if a first person listed a secondperson as a member of the first person's social network, then the priorart doesn't provide a way to consult the second person as a way toconfirm the relationship. The art therefore needs a more accurate methodfor determining the directionality of a social-network link.

Relatedly, prior-art internet search engines are typically designed tomatch search criteria—general words, names, phrases, etc.—with a list of“best fit” websites, based upon keywords and the popularity of thewebsites. The recent application of social networks to such searchengines has introduced the concept of including evaluation of websitesby an individual's contacts in the ranked presentation of the “best fit”websites. There still, however, remains a need in the art for anelectronic search engine that can both: identify individuals in a fieldof interest that have knowledge regarding the searched topic and how thesearcher is connected through a set of intermediaries to the individualthat possesses the knowledge, and allows the searcher to ascertain thedegree to which the person and information can be trusted.

Prior-art methods for performing broadcast searches of data are wellknown. And broadcast searching is widely used in many areas oftechnology today. Broadcast searching can generally be described as asearch method that searches all available searchable data in an effortto locate the sought-after data. Broadcast searching can be slow andcumbersome, and there is therefore a need in the art for an additionalsearch method for searching collections of databases and socialnetworks.

SUMMARY OF THE INVENTION

In general, the present invention provides a method for making aninferential network, the method comprising the step: creating aninferential link between a first inferential-network node and a secondinferential-network node, wherein the inferential link is created as afunction of search data.

The present invention further provides a method for decreasing thestrength of the inferential link, the method comprising the step:decreasing the strength of an inferential link as a function of time.

The present invention further provides a method for increasing thestrength of an inferential link, the method comprising the step:increasing the strength of an inferential link from aninferential-network search-initiator node to an inferential-networkanchor-database node, wherein the strength of the inferential linkincreases as a function of the number of directed searches that thesearch initiator performs using the same search term or search topic incombination with the same anchor database.

The present invention further provides a method for making aninferential network, the method comprising the step: creating aninferential-network node, wherein the inferential-network node iscreated as a function of search data.

The present invention further provides a method for qualifying a node inan inferential network, the method comprising the step: qualifying anode in an inferential network as a function of the strength of one ormore inferential links in one or more inferential networks.

The present invention further provides a method for establishing aninferential-network path, the method comprising the step: establishingan inferential-network path from a first inferential-network node to asecond inferential-network node, wherein the path is selected from oneor more paths in an inferential network.

The present invention further provides a method comprising the step:providing a historical list of directed-search search terms ordirected-search search topics that were anchored to an anchor database.

The present invention further provides a method for making aninferential-network path, the method comprising the step: substituting aportion of a first inferential network with at least a portion of asecond inferential network.

The present invention further provides a method for making aninferential network, the method comprising the step: grafting a sectionof a first inferential network onto a node in a second inferentialnetwork.

The present invention further provides a method for simultaneouslydisplaying inferential-network search results and website searchresults, the method comprising the steps: using a first portion of avisual display screen to display a first window that shows the resultsof an inferential-network search; and using a second portion of thevisual display screen to display a second window that shows the resultsof a website search.

The present invention further provides a method for simultaneouslydisplaying inferential-network search results and social-network-mapresults, the method comprising the steps: using a first portion of avisual display screen to display a first window that shows the resultsof an inferential-network search; and using a second portion of thevisual display screen to display a second window that shows the resultsof a social-network-map data search.

The present invention further provides a method for displaying a portionof an inferential network, the method comprising the step: displaying atleast a portion of an inferential network, wherein the portion of theinferential network is made up at least in part by a section having theform:

-   -   wherein “D₁” is a first inferential-network node,    -   wherein “D₂” is a second inferential-network node,    -   wherein “-” represents an inferential link between D₁ and D₂,        and    -   wherein “n” is a number that qualifies the inferential link.

The present invention further provides a method for displaying a portionof an inferential network, the method comprising the step: displaying atleast a portion of an inferential network, wherein the portion of theinferential network is made up at least in part by a section having theform:

-   -   wherein “D₁” is a first inferential-network node,    -   wherein “D₂” is a second inferential-network node,    -   wherein “-” represents an inferential link between D₁ and D₂,    -   wherein “c” represents a color designation of the “-” link        between the first inferential-network node and the second        inferential-network node, and    -   wherein the color designation of the “-” link qualifies the link        as any of two or more possible link qualifications.

The present invention further provides a method for qualifying aninferential link between a first database and a second database, themethod comprising the step: using a visual indicator to designate atleast one of two or more link qualifications between a first node and asecond node in an inferential network.

The present invention further provides a method for making aninferential-network path, the method comprising the step: substituting afirst portion of an inferential network into a second portion of theinferential network.

The present invention further provides a method for making aninferential network, the method comprising the step: grafting a firstsection of an inferential network onto a node in a second section of theinferential network.

The present invention further provides a method for using a single termor phrase to initiate a multi-term search of an inferential network, themethod comprising the step: searching an inferential network formultiple terms or phrases by initiating a multi-term search of thenetwork using one search term or phrase, wherein the one search term orphrase initiates the use of one or more second search terms or searchphrases in the search.

The present invention further provides a method for ordering searchresults, the method comprising the step: ordering search results as afunction of inferential-network data.

The present invention further provides a method for performing adirected search, the method comprising the step: initiating a directedsearch from a single search field, wherein the single search field hasboth a directed-search search term and a term that identifies an anchordatabase, wherein a differentiator is used to differentiate thedirected-search search term from the term that identifies the anchordatabase, and wherein the differentiator is also used to indicate whichof the two terms is the directed-search search term and which of the twoterms is the term that identifies an anchor database.

The present invention further provides a system for making aninferential network, the system comprising: means for creating aninferential link between a first inferential-network node and a secondinferential-network node, wherein the inferential link is created as afunction of search data.

The present invention further provides a system for decreasing thestrength of the inferential link, the system comprising: means fordecreasing the strength of an inferential link as a function of time.

The present invention further provides a system for increasing thestrength of an inferential link, the system comprising: means forincreasing the strength of an inferential link from aninferential-network search-initiator node to an inferential-networkanchor-database node, wherein the strength of the inferential linkincreases as a function of the number of directed searches that thesearch initiator performs using the same search term or search topic incombination with the same anchor database.

The present invention further provides a system for making aninferential network, the system comprising: means for creating aninferential-network node, wherein the inferential-network node iscreated as a function of search data.

The present invention further provides a system for qualifying a node inan inferential network, the system comprising: means for qualifying anode in an inferential network as a function of the strength of one ormore inferential links in one or more inferential networks.

The present invention further provides a system for establishing aninferential-network path, the system comprising: means for establishingan inferential-network path from a first inferential-network node to asecond inferential-network node, wherein the path is selected from oneor more paths in an inferential network.

The present invention further provides a system comprising: means forproviding a historical list of directed-search search terms ordirected-search search topics that were anchored to an anchor database.

The present invention further provides a system for making aninferential network, the system comprising: means for substituting aportion of a first inferential network with at least a portion of asecond inferential network.

The present invention further provides a system for making asocial-network map, the system comprising: means for grafting a sectionof a first inferential network onto a node in a second inferentialnetwork.

The present invention further provides a system for simultaneouslydisplaying inferential-network search results and website searchresults, the system comprising: means for using a first portion of avisual display screen to display a first window that shows the resultsof an inferential-network search; and means for using a second portionof the visual display screen to display a second window that shows theresults of a website search.

The present invention further provides a system for simultaneouslydisplaying inferential-network search results and social-network-mapsearch results, the system comprising: means for using a first portionof a visual display screen to display a first window that shows theresults of an inferential-network search; and means for using a secondportion of the visual display screen to display a second window thatshows the results of a social-network-map data search.

The present invention further provides a system for displaying a portionof an inferential network, the system comprising: means for displayingat least a portion of a collection of linked databases, wherein theportion of the collection of linked databases is made up at least inpart by a section having the form:

-   -   wherein “D₁” is a first database or node in an inferential        network,    -   wherein “D₂” is a second database or node in an inferential        network,    -   wherein “-” represents an inferential link between D₁ and D₂,        and    -   wherein “n” is a number that qualifies the inferential link.

The present invention further provides a system for displaying a portionof an inferential network, the system comprising: means for displayingat least a portion of an inferential network, wherein the portion of theinferential network is made up at least in part by a section having theform:

-   -   wherein “D₁” is a first database or node in an inferential        network,    -   wherein “D₂” is a second database or node in an inferential        network,    -   wherein “-” represents an inferential link between D₁ and D₂,    -   wherein “c” represents a color designation of the “-” link        between the first database and the second database, and    -   wherein the color designation of the “-” link qualifies the link        as any of two or more possible link qualifications.

The present invention further provides a system for qualifying aninferential link between a first database and a second database, thesystem comprising: means for using a visual indicator to designate atleast one of two or more link qualifications between a first node and asecond node in an inferential network.

The present invention further provides a system for making aninferential-network path, the system comprising: means for substitutinga first portion of an inferential network into a second portion of theinferential network.

The present invention further provides a system for making aninferential network, the system comprising: means for grafting a firstsection of an inferential network onto a node in a second section of theinferential network.

The present invention further provides a system for using a single termor phrase to initiate a multi-term search of an inferential network, thesystem comprising: means for searching an inferential network formultiple terms or phrases by initiating a multi-term search of thenetwork using one search term or phrase, wherein the one search term orphrase initiates the use of one or more second search terms or searchphrases in the search.

The present invention further provides a system for performing adirected search, the system comprising: means for initiating a directedsearch from a single search field, wherein the single search field hasboth a directed-search search term and a term that identifies an anchordatabase, wherein a differentiator is used to differentiate thedirected-search search term from the term that identifies the anchordatabase, and wherein the differentiator is also used to indicate whichof the two terms is the directed-search search term and which of the twoterms is the term that identifies an anchor database.

DEFINITIONS

A seed database is a database within a collection of linked databases,wherein the seed database acts as an originating database from which allother databases stem. Stated differently, a seed database is a databasethat is a central hub in the collection of databases, and all otherdatabases within the collection are linked either directly or indirectlyto the seed database.

A direct link between databases occurs where there are no interveningdatabases between two linked databases. An example of a direct link isprovided:

wherein each D represents a database.

An indirect database link occurs where there is at least one interveningdatabase between two databases that are indirectly linked. An example ofan indirect link is provided:

wherein D_(z) are databases that are indirectly linked;

wherein each D represents a database; and

wherein n is an integer greater than or equal to 1.

A nonlimiting example of indirectly linked databases, wherein there arethree intervening databases, is provided:D_(z)-D-D-D-D_(z)

In one embodiment, a social-network search anchor can generally bedescribed as a first-degree contact in a searcher's social network thatthe searcher designates as being likely to possess information on aparticular subject that is being searched or know of someone who does.In another embodiment, a social-network search anchor is a first-degreecontact in a searcher's social network that the searcher designates asbeing likely to have a social-network profile containing data related toat least a portion of the sought-after data. The search anchor acts asthe database/node to which all other databases/nodes are compared whenmaking the relative determination of which database/node is to besearched next when conducting a directed search.

A search anchor can generally be described as a database that thesearcher designates as being likely to possess information on aparticular subject that is being searched or be directly linked to adatabase that has the information on a particular subject that is beingsearched. Additionally, a search anchor is a database that the searcherdesignates as being likely to have searchable data that is related to atleast a portion of the sought-after data. The search anchor acts as thedatabase/node to which all other databases/nodes are compared whenmaking the relative determination of which database/node is to besearched next when conducting a directed search.

In an additional embodiment a social-network search anchor is afirst-degree contact in a searcher's social network that the searchersdesignates as being most likely, relative to all of the searcher'sfirst-degree contacts, to have a social-network profile containing datathat will match at least a portion of the search topic or search string.In another embodiment, a social-network search anchor is a first degreenode that is designated as being likely to be directly or indirectlyconnected to personal-communication-network members or nodes who havethe sought-after information.

A social-network profile can generally be described as informationrelating to a social-network member. In one embodiment, a social-networkprofile is made up of information that has been input by thesocial-network member. In another embodiment, the social-network profileis itself a searchable database.

A personal-communication-network member is a person that is a node in apersonal communication network.

An opinion leader is a person that has an above-average ability toinfluence people in a field of interest.

A field of interest is an area of specialization.

Personal-communication-network data is any information related to orgenerated from a personal communication network. Nonlimiting examples ofpersonal-communication-network data include: electronic invitations tocurrent and/or new members of a personal-communication network, archivesof personal-communication-network communications, persons that arepersonal-communication-network members, a communication generated fromor directed to personal-communication-network member, apersonal-communication-network member's FAQ's data, archived searchterms generated by a personal-communication-network member, apersonal-communication-network member's field of interest, keywords usedby a personal-communication-network member, phrases used by apersonal-communication-network member, personal-communication-networkmember names, a personal-communication-network member's specialty orfield of interest, the context of a communication to or from apersonal-communication-network member, a personal-communication-networkmember's geographic location, schools attended or general educationalbackground information of a personal-communication-network member, apersonal-communication-network member's graduation year, apersonal-communication-network member's work location or place ofbusiness, a personal-communication-network member's profession, apersonal-communication-network member's insurance information, apersonal-communication-network member's clinical interests, apersonal-communication-network member's research interests, apersonal-communication-network member's patients or clients, or anycombination thereof.

A personal communication network is a type of social network that isdirected to and based upon communication links between nodes. Acommunication link can generally be described as a link between a firstnode and a second node, wherein the communication link is established orbased upon the communication subject matter between the two nodes. Notethat the link is not based solely upon the fact that a first node knowsa second node, but instead the link is directed to a common field ofinterest between the first and second node. Further, a personalcommunication network is directed to identifying to whom apersonal-communication-network member talks to regarding a particularsubject or field of interest. Because a personal communication networkhas communication links that have been created based upon who a nodecommunicates with and seeks advice from or gives advice to regarding thecommon field of interest, personal communication networks are alsocommonly referred to as trust networks.

A common field of interest is a field of interest that is shared by twoor more people.

A person has a personal-communication-network membership when a personis a node in a personal communication network.

Keyword searching is a manner of searching that uses a string ofcharacters in the search term or search phrase.

A third-degree contact is a social-network member orpersonal-communication-network member that isthree-degrees-of-separation away from a specific member or node.

A second-degree contact is a social-network member orpersonal-communication-network member that is two-degrees-of-separationaway from a specific member or node.

A first-degree contact is a social-network member orpersonal-communication-network member that is one-degree-of-separationaway from a specific member or node.

Degrees of separation is a term that describes the relative position oftwo nodes in a social network. A second node is one degree of separationaway from a first node if the second node is directly linked to thefirst node; stated differently, a second node is one degree ofseparation away from a first node if there are no other network nodesintervening between the second node and the first node. Further, asecond node is two degrees of separation away from a first node if thereis exactly one network node intervening between the second node and thefirst node. Still further, a second node is three degrees of separationaway from a first node if there are exactly two network nodesintervening between the second node and first node. Yet further, asecond node is n degrees of separation away from a first node if thereare n−1 intervening network nodes between the second node and the firstnode.

A person's quantity of memberships in personal communication networksequals the number of times a person is identified as a node in one ormore personal communication networks.

A node is a person that is a member of a social network or personalcommunication network.

The frequency of communication describes the number of communicationsbetween two people or two nodes over a period of time.

Direction of communication is a term that describes who sent acommunication and who received the communication. The direction ofcommunication is from the sender of a communication to the recipient ofthe communication.

Innovativeness is a relative term that describes the degree to which anindividual is relatively earlier in adopting new ideas than otherindividuals that are members of a social system. Further, innovativenessis a characteristic that describes an individual's receptiveness inadopting a new innovation relative to other members of the population.Innovativeness depends upon many variables; and nonlimiting examples ofthose variables include risk-taking tendencies and knowledge ofinnovation. The levels of innovativeness (in decreasing order) are:innovators, early adopters, early majority, late majority, and laggards.Innovativeness can also describe an entity's receptiveness in adopting anew innovation relative to other entities. Nonlimiting examples of suchentities include a consumer, hospital, corporation, insurance company,medical practice, and the like.

A personal-communication-network invitation is an invitation thatinvites a person or invitee to become a member or node of a personalcommunication network.

The directionality of a link (or direction of a link) is a term thatdescribes a personal-communication-network link or social-network link.The directionality of a link is based upon identifying the person thatboth received and accepted a social-network invitation orpersonal-communication-network invitation from the sender of thesocial-network invitation or personal-communication-network invitation.The directionality or direction of a link is from the sender of theinvitation to the recipient/acceptor of the invitation. Stateddifferently, the directionality or direction of a link is from theinviter to the invitee, and upon accepting an invitation from theinvitor, the invitee becomes a member of the invitor's personalcommunication network or social network.

A link is a path or connection from one node to another node.

Unidirectional is a term that describes a link between a first node anda second node, wherein the first node has accepted apersonal-communication-network invitation from the second node, but thesecond node hasn't accepted a personal-communication-network invitationfrom the first node. In such a case, a link has been established onlybased upon the first node's acceptance of an invitation from the secondnode.

Bi-directional is a term that describes a link between a first node anda second node, wherein the first node has accepted apersonal-communication-network invitation from the second node, and thesecond node has accepted a personal-communication-network invitationfrom the first node. In such a case, a link has been established basedupon two invitations and acceptances of invitations: the first node'sacceptance of an invitation from the second node, and the second node'sacceptance of an invitation from the first node.

A personal-communication-network link is a link in apersonal-communication-network.

Reciprocal invitation is a return invitation that is sent from anoriginal recipient or invitee back to the original sender or inviter.

An invitation-and-acceptance process is a series of events that enablesa person to become a member of a social network or personalcommunication network.

Mapping is a term that can be used to describe the manner in which asocial network, inferential network, personal communication network, orany other collection of linked databases is visually illustrated.

A real-time online network is an online network that manipulates (e.g.records, analyzes, and presents) data in real time.

Local information can be defined as information possessed by people ordatabases that are directly linked to the searcher initiator.

Linked databases are databases that are connected to each other in somemanner. In one embodiment, databases are linked electronically.

In at least one embodiment, the term user is used to describe apersonal-communication-network member or other authorized individual whois has been invited to join a personal communication network by apersonal-communication-network member and use the system of the presentinvention to communicate with other personal-communication-networkmembers.

In at least one embodiment, a personal-communication-network member isused to describe an individual who has previously joined a personalcommunication network and has saved a profile of himself/herself in acomputer-accessible memory that can be accessed to electronically storeinformation to be used with the system.

An inferential-network search-initiator node is a node in an inferentialnetwork that represents a search initiator that is has initiated adirected search of a collection of linked databases.

An inferential-network anchor-database node is a node in an inferentialnetwork that represents an anchor database that has been used in adirected search of a collection of linked databases.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is an illustrated arrangement of a network for employing thesystem of the present invention.

FIG. 2 is an illustrative display of an embodiment of the presentinvention.

FIG. 3 is an illustrative display of an embodiment of the presentinvention.

FIG. 4 is an illustrative display of an embodiment of the presentinvention.

FIG. 5 is an illustrative display of an embodiment of the presentinvention.

FIG. 6 is an illustrative display of an embodiment of the presentinvention.

FIG. 7 is an example of arrangements on search results.

FIG. 8 is an illustrative relationship between members of a personalcommunication network.

FIG. 9 is an illustrative display of an embodiment of the presentinvention.

FIG. 10 is an illustrative display of an embodiment of the presentinvention.

FIG. 11 is an illustrative display of an embodiment of the presentinvention.

FIG. 12 is an illustrative display of an embodiment of the presentinvention.

FIG. 13 is an illustrative display of an embodiment of the presentinvention.

FIG. 14 is an illustrative display of an embodiment of the presentinvention.

FIG. 15 is an illustrative display of an embodiment of the presentinvention.

FIG. 16 is an illustrative display of an embodiment of the presentinvention.

FIG. 17 is an illustrative display of an embodiment of the presentinvention.

FIG. 18 is an illustrative display of an embodiment of the presentinvention.

FIG. 19 is an illustrative display of an embodiment of the presentinvention.

FIG. 20 is an illustrative display of an embodiment of the presentinvention.

FIG. 21 is an illustrative display of an embodiment of the presentinvention.

FIG. 22 is an illustrative display of an embodiment of the presentinvention.

FIG. 23 is an illustrative display of an embodiment of the presentinvention.

FIG. 24 is an illustrative display of an embodiment of the presentinvention.

DETAILED DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS

This invention is generally directed to a collection or collections oflinked databases. An embodiment of this invention is directed toinferential networks and using inferential networks to analyze datagenerated from directed searches of collections of linked databases.Further, this invention is directed to social-network maps,social-network-map data, and social-network analysis. One embodiment isgenerally directed to social-network analysis of a personalcommunication network or personal communication networks. This inventionis also directed to systems and methods relating to collections oflinked databases. An embodiment of the present invention provides asystem for classifying at least one personal communication-networkmember as an opinion leader in a field of interest based at least inpart on personal-communication-network data. An additional embodiment ofthis invention is directed to performing a directed search ofcollectively linked databases or nodes in order to identify at least onedatabase or node having information on the search topic.

As mentioned above, an embodiment of this invention provides a systemfor classifying at least one personal-communication-network member as anopinion leader in a field of interest based at least in part onpersonal-communication-network data. The system includes acomputer-accessible memory for storing computer-readable logic thatenables a central processing unit (“CPU”) to identify an opinion leaderwithin a field of interest. The CPU can be provided at the server, thecomputer terminal that the user enters data, or any other computationaldevice. The identification of an individual as an opinion leader can bebased upon data generated from the person's participation or interactionwith a personal communication network, such as the person's discussionof a particular topic with another member of that person's personalcommunication network, or merely a membership in the at least onepersonal communication network.

In one embodiment, an opinion leader is a member of apersonal-communication network that has established direct communicationwith many other members of the network. Direct communication requiresthe members to be related by a single degree of separation. Beingseparated by only a single degree of separation, the opinion leader willbe a primary contact of many network members. The more members of thenetwork that have the opinion leader as a primary contact, the higherhis priority, rank, or reputation, as an opinion leader in that networkwill be. A predetermined number of primary contacts can be determinedand set as the threshold number of contacts required to be considered anopinion leader, or opinion leaders can be selected based on the numberof network members they communicate directly relative to other networkmembers.

A single network member can be identified as the only opinion leader pernetwork, that single network member having the most established contactsseparated by a single degree of separation in the particular network.Alternately, a plurality of network members can be selected as opinionleaders, the plurality of network members comprising the top x networkmembers in terms of the number of established contacts separated by asingle degree of separation in that network.

According to other embodiments of the present invention, an opinionleader or a plurality of opinion leaders can be selected based on thepercentage of network members that have received one or morecommunications from the opinion leader(s). According to yet anotherembodiment, an opinion leader can be selected as such based on theoverall number of contacts established, regardless of the particularnetwork in which those contacts are established, quantity and directionof invitations linking the opinion leader to other network members,initiation and outcomes of searches conducted by opinion leaders andother members of the network.

An additional embodiment provides for identifying an opinion leaderusing personal-communication-network data that is based upon or relatedto an invitation-and-acceptance process. More specifically, thepersonal-communication-network data that is based upon or relates to aninvitation-and-acceptance process can be data relating to electronicinvitations to current or new members of a personal communicationnetwork.

A further embodiment provides for identifying an opinion leader usingpersonal-communication-network data that is based upon or related tosearch terms or phrases employed by a personal-communication-networkmember in conducting a search of personal-communication-network data.

Defined as above, an opinion leader is considered to be a network memberwhose opinions reach a large audience relative to the opinions of othermembers of that network. Typically, the opinion leader's comments havegrown to be well respected in a particular field over time due at leastin part to the knowledge, experience, or familiarity with the subjectmatter on which the opinion leader comments. This respect, in turn,motivates physicians or others seeking to gain knowledge about thissubject matter to invite the opinion leader to join their personalnetwork as a primary contact, separated by only one degree ofseparation. As the number of network members that list the opinionleader as a primary contact increases, so does the opinion leader'sprospective audience and therefore, his ability to influence theknowledge of those audience members.

The system for classifying at least one personal-communication-networkmember as an opinion leader can optionally identify, or otherwiseclassify at least one personal-communication-network member as anopinion leader in a field of interest based upon the quantity ofmemberships that the at least one personal-communication-network memberhas in personal communication networks, wherein all of the networks havethe field of interest in common. Thus, one or more opinion leaders canbe identified specifically for the particular field of interest.

Computer-readable logic can optionally be provided according to anembodiment of the present invention to identify or classify a person asan opinion leader within a field of interest based upon the quantity ofelectronic communications that the person has sent topersonal-communication-network members in the field of interest.Likewise, the one or more opinion leaders can be identified andclassified according to instructions within computer-readable logic thatclassifies a person as an opinion leader within a field of interestbased upon the quantity of electronic communications that the person hasreceived from personal-communication-network members in the field ofinterest. Alternate embodiments consider a combined number of sent andreceived electronic communications to identify an opinion leader. Otherfactors, such as the direction and quantity of invitations orconnections between nodes, frequency of communication between nodes, thenumber of words in a communication between nodes, the direction ofcommunication between nodes, the number of key words in a communicationbetween nodes, the search terms and results generated by the nodes, andcombinations thereof, for example, can also be used in addition to, orin lieu of, any other factor mentioned above.

An alternate embodiment of the present invention provides a system forassessing a person's likelihood to use a concept or product that is newto the person. The system includes computer-readable logic forclassifying a person's innovativeness based upon the quantity ofpersonal-communication-network invitations the person has received froma personal-communication-network member.

A network member considered to be an innovator, as that term is usedherein, is a network member who is more likely to adopt, or otherwiseadapt his practice to include a novel technology, treatment, therapeuticagent, ideology, or other advance (collectively referred to as a “recentdevelopment”) than other network members who are not innovators. Similarto the description above for identifying an opinion leader, an innovatorcan be selected as the network member who is likely to be the first toadopt a recent development, or as the top y network members who arelikely to be the first y people to adopt the recent development.Alternately, the innovator(s) of a particular network can be identifiedas the z % of network members who are likely to adopt a recentdevelopment within a predetermined timeframe. These are but a fewexamples of the many possible ways to identify the innovator(s) of anetwork, and should not be considered an exhaustive listing of allpossibilities.

Any factor that tends to indicate a network member's likelihood to adoptor otherwise utilize a given recent development can be used to identifythe innovator(s) of that network. Nonlimiting examples of such factorsinclude: the time between a similar recent development's introduction tothe market and a time when the network member adopted the similar recentdevelopment; the network member's participation in experimental studies;the length of time required for the person to respond to apersonal-communication-network invitation; the duration of prescriptionswritten by network members; the number of invitations sent to apotential user/member; publications by the network member discussingefforts to develop the recent development; anticipation of the recentdevelopment; opinions expressed by opinion leader(s); or opinions byother network members respected by the network member. Any of thefactors chosen to identify the innovator(s) of a network can be suitablyweighted to fine tune the algorithm used to quantify the degree ofinnovativeness used to identify innovators.

As mentioned above, innovativeness can be classified based upon thenumber of invitations sent to a potential user/member, wherein theinvitations are directed to the invitee joining a social network or apersonal-communication network. Some individuals may require only oneinvitation to convince them to join—these are the innovators. Others mayrequire up to ten or fifteen invitations from current users beforedeciding to join—these are the laggards. Innovativeness classificationscan be used in marketing campaigns in which innovators can be targetedfirst, then early adopters, early majority, late majority, and laggards(innovators being the most innovative and laggards being the leastinnovative).

In one embodiment for classifying a person's innovativeness, aninnovativeness classification is arrived at by using computer-readablelogic that employs a function that is based uponpersonal-communication-network data in combination with a statisticaldiffusion curve and innovativeness classifications (as defined bydiffusion researchers). In one embodiment, the statistical diffusioncurve is an s-shaped curve that plots the percentage of a populationthat has adopted an innovation over time. In theory (and as verified bydata), once the percent of population adopting an innovation hitsroughly 20%, the rate of adopting rapidly increases, and then tapers offas the percent of population adopting the innovation hits about 80%.

It is common for opinion leaders to also be considered innovatorsbecause of the personality traits common amongst authoritative figuresin a particular field and innovators in that same field. Accordingly,whether a network member is considered to be an opinion leader canoptionally be a factor used to determine whether that network member isalso an innovator.

In addition to the above, at least one embodiment of this inventionprovides for searching personal-communication-network data that is inthe form of electronic or electronically searchable communicationsbetween personal-communication-network members. An embodiment thatemploys the search method provides computer-readable logic fordetermining or identifying the use of one or more words or phrases in acommunication or communications between twopersonal-communication-network members. Computer-readable logic can beused to search for a string of characters within one or more databasesof recorded electronic or electronically searchable communication(s)from one personal-communication-network member to another. Thecomputer-readable logic searches the personal-communication-networkcommunications and quantifies or qualifies the use of at least onestring of characters, e.g., word or phrase, within the communications.

An additional embodiment of this invention provides for usingcomputer-readable logic to search personal-communication-network datathat is in the form of electronic or electronically searchablecommunications between personal-communication-network members or nodes.A use of such an embodiment can be directed to identifying a topic ofdiscussion or common field of interest between two or morepersonal-communication-network members. This embodiment provides forusing computer-readable logic to search one or more databases ofrecorded electronic or electronically searchable communication(s)between personal-communication-network communications for words orphrases associated with a search term or search phrase. Thecomputer-readable logic identifies the words or phrases relating to afield of interest and can thereby identify a topic of discussion orfield of interest in a particular communication or communications.

In an embodiment of the invention, personal-communication-network datain any known form of communication can be subject to SNA viacomputer-readable logic. In a further embodiment,personal-communication-network data in any known form of electronic orelectronically-searchable communication can be subject to SNA viacomputer-readable logic. Nonlimiting examples of useful forms of knownelectronic or electronically-searchable communications include:electronic mail (email), chat, online chat, and discussion boards.

Further, regarding the above-mentioned communication between nodes,another embodiment uses computer-readable logic to identify and definecommunication contexts among personal-communication-network users.Stated differently, the embodiment identifies one or more topics ofdiscussion within a communication between two nodes. The communicationcontexts will most likely be dependent upon the audience and networkboundary. In an example relating to the medical domain, nonlimitingexamples of communication contexts or general topics of discussioninclude: medicine, pediatrics, aerospace medicine, diagnosis andtreatment, pharmacology, asthma, allergy and immunology, anesthesiology,colon and rectal surgery, dermatology, emergency medicine, familypractice, general preventive medicine, internal medicine, critical caremedicine, medical genetics, neurology, physical medicine andrehabilitation, preventive medicine, psychiatry, molecular geneticpathology, neurological surgery, diagnostic radiology, neuroradiology,nuclear medicine, obstetrics, gynecology, occupational medicine,opthalmology, orthopaedic surgery, otolaryngology, pathology-anatomicand clinical pediatrics, plastic surgery, preventive medicine, publichealth, radiation oncology, radiology-diagnostic surgery, thoracicsurgery, urology, abdominal radiology, addiction psychiatry, adolescentmedicine, adult reconstructive orthopaedics, blood banking/transfusionmedicine, cardiothoracic radiology, cardiovascular disease, chemicalpathology, child neurology, clinical cardiac electrophysiology, clinicalneurophysiology, clinical and laboratory immunology, craniofacialsurgery, critical care medicine, cytopathology, dermatopathology,developmental-behavioral pediatrics, endovascular surgicalneuroradiology, foot and ankle orthopaedics, forensic pathology,forensic psychiatry, gastroenterology, geriatric medicine, geriatricpsychiatry, hand surgery, hematology, oncology, infectious disease,interventional cardiology, medical microbiology, medical toxicology,musculoskeletal oncology, musculoskeletal radiology, neonatal-perinatalmedicine, nephrology, neurodevelopmental disabilities, neuropathology,neuroradiology, neurotology, nuclear radiology, oncology, orthopaedicsports medicine, orthopaedic surgery of the spine, orthopaedic trauma,pain medicine, pediatric anesthesiology, pediatric cardiology, pediatriccritical care medicine, pediatric emergency medicine, pediatricemergency medicine, pediatric endocrinology, pediatric gastroenterology,pediatric hematology/oncology, pediatric infectious diseases, pediatricnephrology, pediatric orthopaedics, pediatric otolaryngology, pediatricpathology, pediatric pulmonology, pediatric radiology, pediatricrehabilitation medicine, pediatric rheumatology, pediatric sportsmedicine, pediatric surgery, pediatric urology, procedural dermatology,pulmonary disease, rheumatology, selective pathology, spinal cordinjury, sports medicine, surgical critical care, undersea and hyperbaricmedicine, vascular neurology, vascular surgery, vascular andinterventional radiology, or a combination thereof.

In another embodiment for using computer-readable logic to identify anddefine communication contexts or general topics of discussion amongpersonal-communication-network users, employable communication contextscan include any or all fields of interest. For example, if the networkinvolves consumers, and a user or member wants to know what socialnetwork or personal-communication-network members are “opinion leaders”on the topic of cars (i.e. who do most consumers consult before buying acar), then one communication context should be for example“automotives.” Additional nonlimiting examples of general communicationcontexts, topics of discussion, or fields of interest include: medicine,sports, science, performing arts, mathematics, literature,pharmaceuticals, biotechnology, health sciences, nursing, automotive,social work, dentistry, occupational therapy, physical therapy,rehabilitation counseling, gerontology, health administration,optometry, veterinary medicine, natural sciences, biology, chemistry,physics, forensic science, political science, history, anatomy,biostatistics, physiology, social sciences, philosophy, psychology,sociology, anthropology, education, research, mental health,psychotherapy, health, fitness/exercise, nutrition/diet,athletics/sports, games, hobbies, therapy, engineering, statistics,literature, politics, local government, state government, federalgovernment, advocacy, law, law enforcement, private investigation,military science, journalism, mass communications, consulting, projectmanagement, contracting, architecture, religion, spirituality, culture,fine arts, performing arts, art history, dance and choreography, fashiondesign, interior design, painting, photography, filmmaking, sculpture,theatre, music, martial arts, crafts, entertainment, food, technology,information systems, electronics, business, marketing, management,accounting, economics, finance, entrepreneurship, automotive, realestate, home ownership, insurance, home furnishings, manufacturing,shipping, retail, beauty, fashion, environmental science, nature,animals, pets, botany, agriculture, security, aviation, travel or acombination thereof.

Still another embodiment provides for evaluating a relationship betweentwo personal-communication-network members wherein computer-readablelogic searches one or more databases of personal-communication-networkdata, including communications between thepersonal-communication-network members and performs one or all of thefollowing: quantify the number of communications between the members,determine the frequency of electronic communication between the members(frequency can be described in terms of the dimension-number ofcommunications per unit time), recording the number of words in anelectronic communication between the members, recording the direction ofcommunication between the members, recording the use of keywords in anelectronic communication between the members, or a combination thereof.

The present invention further includes a “social search engine” thatallows social-network or personal-communication-network members tosearch within their networks for other personal communication members ornodes that have access to information that they are seeking. The searchcomponent of the embodiment includes computer-readable logic thatperforms the function of a filtering mechanism, whereby a network memberperforming a search can use the social search engine's computer-readablelogic to search her social network or personal communication network formembers that have or are likely to have information of the searchedsubject. In a further embodiment, all of the search-string informationinput by a member conducting a search is stored in a searchable databaseand thereby adds to the personal-communication-network data generated bythe member. This may be helpful because it may be beneficial to knowwhat search terms or phrases are most often used by that or othernetwork members.

In one embodiment for searching personal-communication-network data, thesearch can be directed to a field of interest or characteristics ofpersonal-communication-network members. The search can be as general as“automotives,” or as specific as “females between the ages of 12 and14.” A nonlimiting list of other potentially searchable topics include:behaviors, needs, desires, trends, and norms.

This invention also provides for using computer-readable logic thatsearches personal-communication-network data for multiple terms orphrases by initiating the search with a single search term. In otherwords, an embodiment is directed to using a single term or phrase toinitiate a multi-term search of personal-communication-network data.Computer-readable logic initiates a multi-term search of thepersonal-communication-network data by first identifying one or moreterms or phrases that will be searched in addition to the single searchterm or phrase that was entered by a user. The computer-readable logicdoes this by associating the single search term or phrase with apredetermined set of additional search terms or search phrases that havebeen preselected to be searched in addition to the single search term orphrase. The computer-readable logic then applies both the single searchterm or phrase and the predetermined set of additional search terms orsearch phrases in a search of one or more databases ofpersonal-communication-network data.

Additionally, if a search term or search phrase used in apersonal-communication-network data search does not literally match anyterms or phrases in the personal-communication-network data, the presentinvention has provided computer-readable logic for matching specificconditions, treatments, pharmaceutical drugs, and medical specialties toselected search terms and phrases. Therefore, computer-readable logicwill search for at least one predetermined search term or phase that hasbeen associated with the initial search term or phrase. And althoughthere may be no literal match to the initial search term, meaningfulsearch results can still be generated based upon the social searchengine's computer-readable logic searching for additional related termsor phrases.

An alternate search embodiment of this invention is directed toinitiating an internet or intranet search from the personal profile of asocial-network member. This embodiment can initiate an internet orintranet search, wherein the search is based at least in part on thename or identity of the social-network member or social-network node.Computer-readable logic can initiate the search by providing for anelectronically executable button in an electronic window that displays aprofile of information or data relating to a specific social-networknode, i.e., social-network member, and when the electronicallyexecutable button is electronically pressed—an internet or intranetsearch is initiated for websites that contain at least a portion of thesocial-network member's name or identity. In addition to initiating aninternet or intranet search using at least a portion of thesocial-network member's name or identify, another embodiment of thisinvention provides for initiating the search using additional searchterms in combination with at least a portion of the social-networkmember's name or identity.

Another embodiment of this invention is directed to initiating asocial-network-map data search from an internet or intranet website.More specifically, this embodiment provides for initiating asocial-network-map data search from an internet or intranet website byproviding an electronically-executable button in the website, whereinwhen the button is electronically pushed the social-network data searchis initiated. The social-network-map data search can be directed to anypiece or amount of data. A nonlimiting example of a social-network-mapdata search includes locating a node in a social-network map thatrepresents a person named or identified in the website.

An embodiment of the invention also provides for a method directed toestablishing a social-network or personal-communication-network linkbetween two people. The invitation-and-acceptance method is directed tosending a social-network or personal-communication-network invitationfrom a personal-communication-network member, i.e. an inviter, to aninvitee. An embodiment of the invitation is directed to making theinvitee a member of the inviter's social network or personalcommunication network. The invitation is not limited to any particularform, but in an embodiment, the invitation is an electronic invitationsuch as an email. The invitation embodiment has the inviter describe acommon field (or fields) of interest between the inviter and invitee.Stated differently, the inviter indicates at least one subject or fieldof interest that the inviter would like to communicate about with theinvitee.

In a further embodiment of the invitation-and-acceptance method, theinvitee is provided with an opportunity to send a reciprocal invitationto the original inviter, wherein the original inviter is invited intothe invitee's social network or personal communication network.

Another embodiment of the invitation-and-acceptance method also providesfor defining the directionality of a link between nodes in apersonal-communication-network based upon an indication of whether anoriginal inviter wants to be a member of an original invitee's personalcommunication network. A social-network orpersonal-communication-network invitation method generally involvessending a social network or personal-communication-network invitationfrom one person to another person, i.e., from and inviter to an invitee.And generally, if the invitee accepts the invitation, then the inviteebecomes a member of the inviter's social or personal communicationnetwork, and thus a unidirectional link is established—from the inviterto the invitee.

An embodiment of this invention provides for automatically providing theperson that is sending a social network orpersonal-communication-network invitation with an option to accept areciprocal invitation from the invitee, should the invitee choose tosend a reciprocal invitation. In other words, an original inviter isprovided with a way to accept in advance a reciprocal invitation fromthe invitee, if the invitee should decide to send a reciprocalinvitation. A nonlimiting example of this embodiment usescomputer-readable logic to automatically provide the person that issending a social network or personal-communication-network invitationwith an option to accept a reciprocal invitation from the invitee.

To promote meaningful links between people having a common field ofinterest, an embodiment of the invention provides for a system thathelps personal-communication-network members construct meaningful trustnetworks by providing explicit instructions for aninvitation-and-acceptance process used to construct a personalcommunication network. The system uses computer-readable logic toprovide a user with conditions for inviting a person into the user'spersonal communication network. As a nonlimiting example of instructionsrelating to a personal communication network directed to the medicalfield, the instructions might read, “Who to invite: Invite colleagueswhose opinions you value and often solicit when making medical decisionsor considering alternative treatments. This network should includephysicians you trust to provide reliable information or advice regardingmedical treatments, practices, and advances for the professionalservices you provide. If you highly value the opinions, judgments,advice, or interpretations of a physician, you should invite them intoyour trust network. What you can learn: Information is only as good asthe source that delivers it. Building this network can help you manageyour current contacts—the physicians you trust and know directly—as wellas help you identify the trusted sources of your trusted colleagues.Expand your opinion network to obtain volumes of valued opinions andreliable information from your colleagues, colleagues' colleagues, orcolleagues' colleagues' colleagues.” The system has computer-readablelogic that will enable the invitation-and-acceptance instructions to beprovided to an inviter that is sending an invitation. These instructionshelp to ensure that data obtained through personal-communication-networklinks are meaningful. As a result, a user can be certain that physiciansin his personal-communication-network trust each other for valuedopinions and advice.

In an embodiment of the invitation-and-acceptance method, apersonal-communication-network member (original inviter) sends aninvitation, which can be an electronic invitation, to an individual(original invitee). The individual may or may not be a member of apersonal communication network, and the invitation invites the inviteeinto the inviter's personal communication network. In composing aninvitation contemplated by this invention, the original inviter canindicate in advance whether, should the inviter receive a reciprocalinvitation into the invitee's trust network, the member would accept ordecline such an invitation.

The system has computer-readable logic for determining whether aninvitee is a current member of a personal communication network; if yes,then in one embodiment an invitation is sent to the invitee's systememail address. A system email address is an email address provided bythe system to a personal-communication-network member. If the invitee isnot a personal-communication-network member, then the invitation is sentto an email address external to the system. Once the invitee reads theemail, she can decide whether to accept or decline the invitation.Should she choose to accept, she can indicate whether she wishes to senda reciprocal invitation to the original inviter. If she chooses to senda reciprocal invitation to the original inviter, the system hascomputer-readable logic that checks for the original inviter's advanceindication for either accepting or declining a reciprocal invitation.

In an embodiment of the invention, if an original inviter has indicatedin advance that they would accept a reciprocal invitation from anoriginal invitee, and the original invitee has both accepted theoriginal invitation and sent a reciprocal invitation, then thecomputer-readable logic establishes a bi-directional link. If anoriginal inviter has indicated in advance that they would accept areciprocal invitation from an original invitee, but the original inviteehas only accepted the original invitation and chosen not to send areciprocal invitation, then the computer-readable logic establishes aunidirectional link from the original inviter to the original invitee.If an original inviter has indicated that they would not accept areciprocal invitation from an original invitee, and the original inviteeaccepts the original invitation, then the computer-readable logicestablishes a unidirectional link from the original inviter to theoriginal invitee.

The invitation-and-acceptance process affords several opportunities forcollecting and storing directional information and confirmation, andsuch information has implications for searches performed by the membersvia the site. As a nonlimiting example, if a receiving physician (e.g.Dr. Smith) accepts and invitation from an inviter physician (e.g. Dr.Jones), then the system stores this link as one from Dr. Jones to Dr.Smith. Furthermore, Dr. Smith becomes a member of Dr. Jones' trustnetwork, and Dr. Jones obtains access to Dr. Smith'spersonal-communication-network data and to the members of Dr. Smith'spersonal communication network. Likewise, if the receiving physician(Dr. Smith) reciprocates the invitation and the sending physician (Dr.Jones) accepts, then the system stores a second link from Dr. Smith toDr. Jones, indicating that Dr. Jones is a part of Dr. Smith's trustnetwork as well. Further, Dr. Jones becomes a member of Dr. Smith'strust network, and Dr. Smith obtains access to Dr. Jones'personal-communication-network data and to the members of Dr. Jones'personal communication network.

In the event that a physician declines an invitation, a link is notestablished, and—although the system stores all invitations anddecisions—trust networks usually reflect the convention that a receivingphysician that accepts an invitation becomes a part of a sendingphysician's trust network.

Physicians may have several different sources of advice and information,which they may or may not approach based upon the topic at hand. Suchtopics may include diagnostic information, treatment recommendations,pharmaceuticals, legal or ethical advice, and the like. Physicians whoare respected advisors in terms of diagnoses may not be the bestphysician to question regarding the latest technological innovations.Therefore, the present invention requires physicians to indicate thetopic(s) about which they consult the physician they wish to invite. Anembodiment of the present invention implements this idea by way of thenonlimiting example:

-   -   Individual to Invite:

First Name: Last Name: Type of Practitioner (MD, DO): Email Address:

-   -   I consult this physician regarding the following: (check all        that apply)

    Pharmacological     Practice Management     Diagnostic    Technology     Policy     Procedure     Ethics     Research    Legal

The consultation topics checked may also be used as a measurement oftrust. For example, if Dr. Gardner indicates that she consults Dr.Harris regarding two topics, but she consults Dr. Johnson regardingfive, then it can be inferred that Dr. Gardner trusts Dr. Johnson morethan Dr. Harris. More importantly, encouraging physicians to indicatethe context of their communication with each physician provides a richand useful database.

A further embodiment of the invention is directed to the manner in whichsocial-search-engine search results are presented. In other words, thefurther embodiment is directed to presenting: 1)personal-communication-network members identified by thepersonal-communication-network data search; and 2) how the members arelinked to the personal-communication-network member performing thesearch. In an embodiment, the search results are presented in a mannerwherein at least one personal-communication-network member is named in asearch result, and at least one network path is presented that displaysa link or series of links that show how thepersonal-communication-network member performing the search is linked tothe at least one personal-communication-network member identified by thesearch. The network path can be a visual depiction of a path from onemember to another member; links between nodes are conventionallyillustrated by strait lines, and nodes are conventionally illustrated bydots or circles.

Still another embodiment of the invention is directed to the manner inwhich social-search-engine search results are presented. Morespecifically, the embodiment presents: 1) personal-communication-networkcommunications identified by the personal-communication-network datasearch; and 2) how the personal-communication-network members thatgenerated the communications are linked to thepersonal-communication-network member performing the search. In otherwords, the presentation of the social-search engine results displays theboth the communications and their source in a visual manner. Asmentioned above, the visual manner of presentation is a depiction of apath from one member to another member; links between nodes areconventionally illustrated by straight lines, and nodes areconventionally illustrated by dots or circles.

Yet another embodiment of this invention is directed to simultaneouslydisplaying social-network-data search results in combination withinternet or intranet search results. In one embodiment, the internet orintranet search results are website search results. One embodiment foraccomplishing this simultaneous display of search results usescomputer-readable logic to use a first portion of a visual displayscreen, e.g., a computer monitor, to display social-network-data searchresults and use a second portion of the visual display screen to displayinternet search results or intranet search results. One embodiment fordisplaying social-network-data search results in combination withinternet or intranet search results uses two separate electronicwindows. Specifically, on a visual-display screen a first electronicwindow is used for displaying social-network-data search results, and asecond electronic window is used for displaying internet search resultsor intranet search results. There is no limitation on the percentages ofa screen that can be used to display either the social-network-datasearch results or the internet or intranet search results. In oneembodiment, at least 50% of the visual display screen is used to displaythe social-network-data search results. In another embodiment, at least10% of the visual display screen is used to display thesocial-network-data search results. In another embodiment, at least 50%of the visual display screen is used to display the internet searchresults or intranet search results. In still another embodiment, atleast 10% of the visual display screen is used to display the internetsearch results or intranet search results.

The present invention will allow personal-communication-network membersto analyze personal-communication-network data to obtain search resultssuch as: degrees (the number of direct connections or first-degreecontacts a personal-communication-network member has), betweenness(represents a bridge between two cliques or clusters in a personcommunication network), closeness (a measurement of how close a personis to everyone else in the network), boundary spanners (have access toideas and information flowing in other clusters—innovators), peripheralplayers (often connected to networks that are not currently mapped),structural equivalence (determine which people play similar roles in thenetwork), cluster analysis (find cliques and other densely connectedclusters), structural holes (find areas of no connection between peoplethat could be used for advantage or opportunity), and E/I Ratio (findwhich groups in the network are open or closed to other).Personal-communication-network members may also find other statisticsuseful that are particular to their field of interest. As a nonlimitingexample, the present invention provides analyses of the percentage of aphysician's personal-communication-network using a particular treatmentand “distance to X,” which allows the physician to determine theshortest path to a target member in the physician's personalcommunication network.

An embodiment of the invention searches personal-communication-networkdata using computer-readable logic that employs mathematical algorithmsto determine the order of presentation of search results. Suchalgorithms take into account keywords entered into eachpersonal-communication-network member's profile, field(s) of interest,the likelihood that the target member is the best person to answer thequestion (based upon personal-communication-network data specific to thetarget member), degrees of separation from the member conducting thesearch (degrees or links away), similarity to the searching member(based upon attributes listed in the profiles), physical proximity, andother personal-communication-network data (such aspersonal-communication-network communications).

Moreover, the search results present the path betweenpersonal-communication-network members, e.g., from thepersonal-communication-network member entering the search terms to thepersonal-communication-network members identified by the search, whichincludes all members in the shortest number of links. Therefore, themember performing the search learns who has the information they seek,the personal-communication-network profile of a member or membersrevealed by the search, and how the members revealed by the search areconnected to the member conducting the search.

In an embodiment, social engine search results are presented in aninnovative, clear, and tabular manner. The social search engine presentsresults by clearly denoting who in a member'spersonal-communication-network has the information being sought and howthe searcher is connected to the members revealed by the search. In anembodiment, the columns represent degrees or links between the searchingmember and the network members revealed by the search. In yet anotherembodiment, the rows illustrate the relational paths from the searchingmember to the member(s) revealed by the search. In a further embodiment,highlighted names indicate a personal-communication-network memberhaving the information sought. In another embodiment, the searchingmember's personal-communication-network profile is shown on the leftpanel of the results table, and the profile of apersonal-communication-network member revealed by the search can beviewed in the right panel by clicking his or her name.

Should the attributes of the personal-communication-network members beof interest, then a personal profile page may be added to the system. Inthis case, members can input various information about themselves (e.g.fields of interest, credentials, resources, publications, or contactinformation).

A further embodiment of the invention provides apersonal-communication-network member with the ability to organizepersonal-communication-network communications by providing thepersonal-communication-network member with computer-readable logic forarchiving personal-communication-network communications into apersonal-communication-network database. The database in turn issearchable by personal-communication-network members, wherein the memberperforming the archiving designates a searchable term to be associatedwith the personal-communication-network archive or communication. Uponassociating the search term with the personal-communication-networkarchive or communication, a keyword search ofpersonal-communication-network data that uses the searchable term willreturn a search result that identifies thepersonal-communication-network archive or communication.

A further embodiment of the invention provides for computer-readablelogic that organizes personal-communication-network invitations to emailaddress provided by the invention. In an embodiment, computer-readablelogic identifies whether an invitee of a personal-communication-networkinvitation is a personal-communication-network member. And if theinvitee is a personal-communication-network member, then thecomputer-readable logic directs an invitation to apersonal-communication-network electronic mailbox (e-mailbox) providedby the invention. Stated differently, if an invitee is apersonal-communication-network member and receives an invitation fromanother personal-communication-network member, then that invitation isautomatically directed or redirected by the computer-readable logic toan e-mailbox provided by the inventive embodiment.

In an embodiment, the invention does not overwritepersonal-communication-network data so as to monitor/record changes inthe personal-communication-network data over time. Changes to thenetwork data are preferably stored as new entries in a database, so allentries and revisions are saved in the database, and this database isaccessible for personal-communication-network data analyses and thelike. Methods of storing electronic data via computers, software,databases, servers, and the like are known and relatively common. In anembodiment of this invention, relational databases that are connected tomultiple servers or server farms can be employed to storepersonal-communication-network data.

In an embodiment, the present invention allows for the collection ofreal-time data. Because an embodiment of the invention provides a systemhaving a server database that stores all information as new—and does notoverwrite outdated data—changes in personal communication networks willbe stored and traceable so that the dynamic and flexiblepersonal-communication-network data can be analyzed for changes overtime. As an example, such changes may include additional links asphysicians invite new physicians, forge new friendships, link tophysicians they meet via a website, at conferences, or new contacts whenthey move. Moreover, the database will reflect the deletion or removalof ties when physicians indicate that a relationship or link no longerexists (for reasons such as moves, death, a “falling-out,” etc.).

In an embodiment, personal information (or network-profile information)can be verified before a person becomes a personal-communication-networkmember. For example, if the target members of a personal communicationnetwork are an exclusive group (i.e. physicians, attorneys, collegestudents, etc.), then the invention may require a verification process,wherein a person's information is verified before the person can becomea personal-communication-network member. This will not only put theusers at ease, but will also ensure the integrity of the collected data.For example, if the social network of attorneys is desired, it isimportant to ensure that only the network of attorneys is captured, andnot the relationships between attorneys, their clients, and theirsecretaries, etc.

Another embodiment of the invention provides a server withcomputer-readable logic for mapping personal-communication-network pathsor links with specificity. In an embodiment, the invention maps two ormore personal-communication-network paths or links. In anotherembodiment, the invention maps three or morepersonal-communication-network paths or links. In another embodiment,the invention maps four or more personal-communication-network paths orlinks. In yet another embodiment, the invention maps five or morepersonal-communication-network paths or links. In still anotherembodiment, the invention maps a plurality ofpersonal-communication-network paths or links. Pragmatically,personal-communication-network members may want to know all paths thatlead from them to a target member for various reasons. Perhaps they haverecently spoken to the member who serves as the link in one path, orthey prefer to utilize a particular member as a link over another forprestige, or one member is on vacation and therefore cannot serve as aliaison. Whatever the reason behind the desire to see multiple paths,the present invention recognizes and satisfies this desire. Sometimesone direct route is all that is needed, but it may be preferable to haveoptions.

In addition to being invited into a personal communication network, auser can elect to register as the start (or seed) of a new personalcommunication network that will initially only include that user. In anembodiment, before a user is permitted to register as a newpersonal-communication-network member, a verification process canoptionally be conducted to ensure that the user attempting to registeris actually interested or involved in a field of interest. For example,a physician may be verified to be board-certified and duly authorized topractice medicine. According to this physician example, to initiate anew personal communication network, and therefore become a physicianwithin a personal communication network, the user can enter anappropriate URL into an address line of a web-browser displayed by aremote computer terminal in a known manner. Upon accessing the systemfor the first time, computer-readable logic causes anew-user-registration option to be displayed to the user. To minimizethe number of unauthorized users that can use the system forunscrupulous purposes, users can register by creating a profile ofthemselves before they are able to log in and conduct a search or takeadvantage of other features of the system. The information entered bythe user can be used to confirm the user's status as a licensedphysician or other authorized user of the system. Returning users thathave already completed their profile can skip the new-user registrationstep by electing to log in instead. Use of the system following a log-inprocedure or after receiving an invitation to join is described indetail below.

In use, an embodiment of the system of the present invention can beaccessed by a user by entering an appropriate URL into an address lineof a web-browser displayed by a remote computer terminal in a knownmanner. Upon being invited to join a personal communication network by apersonal-communication-network member, a user receives an email with ahyperlink to permit the user to access the system for the first time.Executing the hyperlink causes the display of a new-user-registrationinterface generated by computer-readable logic. To minimize the numberof unauthorized users that can use the system for unscrupulous purposes,even invited users can register by creating a profile of themselvesbefore they are able to log in and conduct a search or take advantage ofother features of the system. Returning users that have alreadycompleted their profile can skip the new-user registration step byelecting to log in instead.

After the invited user has created a profile and logged in,computer-readable instructions cause a home page to be displayed so theuser can select from a plurality of options presented as tabs locatedalong an upper portion of the home page. Examples of the optionsavailable to logged-in users as shown in FIG. 3 include Home, Search,Message Center, Invitations, Settings, and Help. FIG. 3 is merely anexample of the system options that can be provided, but the system ofthe present invention can offer at least the Search option.

Once a user has generated his/her profile, the user can extendinvitations to other registered personal-communication-network membersto join the user's personal communication network, and use the Searchoption to locate personal-communication-network members already in theuser's personal communication network and commence communications withthose personal-communication-network members that satisfy theuser-defined search criteria.

Extending an invitation to join the user's personal communicationnetwork can be accomplished by selecting the Invitations tab, whichcauses an Invitation screen generated by computer-readable logic to bedisplayed by the monitor as shown in FIG. 3. An invitation to join apersonal communication network by selecting the Invitations tab can besent by entering an email address, contact name, or other informationidentifying the person or user to be invited into an invitation field.Selecting an Invite button causes the system to convey an invitation viaemail or other electronic communication to join the user's personalcommunication network to the invitee who is identified in the invitationfield.

For the embodiment shown in FIG. 3, the email address is entered in theinvitation field and the Invite button selected. As an example, toillustrate the present invention, the fictitious name and email addressof Dr. Steve Johnson at Fake Hospital is used. The detailed display ofFIG. 4 generated according to the instructions in the computer-readablelogic allows the user to specify the context in which the user willconsult with the other physician to be invited into the user's personalcommunication network. For example, the detailed-invitation screen shownin FIG. 4 allows the user to select one or more of the followingconsultation contexts: Diagnostic, Treatment, Pharmacological, Research,Education, and Practice Management. Any number of these contexts can beeliminated, replaced with other contexts not specifically recitedherein, or supplemented by other contexts without departing from thescope of the present invention.

To assist the user in selecting a proper context for consultation, theuser can view a description of each context by selecting such an optionwith an electronic pointing device such as a conventional mouse ortrackball. In FIG. 4, the (description) option positioned adjacent tothe context for which additional information is sought can be selectedto view the additional information.

When the user is specifying the context in which he/she will consultwith the person or user to be invited, the user can also select whethera reciprocal invitation will automatically be accepted, should theinvited person or user elect to send one. A selection whether to acceptany reciprocal invitation can be made by choosing the check box, or byany other suitable indicia of the user's desire to automatically acceptany reciprocal invitation to join the personal-communication network ofthe invited person or user. And just as before, the user can specify theareas in which the user feels comfortable rendering advice or generallycommunicating.

Sending an invitation to an invitee to join a user's personalcommunication network, and the entire network in general, is an attemptto include that invitee in the personal communication network of theuser in the one or more contexts specified by the user. The invitee willbe the recipient of an email, or other electronically-originatedcommunication informing the invitee of the existence of the invitation.Other embodiments of the present invention include computer-readablelogic that generates a visual notice, audible notice, or a combinedvisual and audible notice to alert the invitee to the existence of theinvitation when the invitee logs onto the system. As shown in FIG. 3, aninvitation table of received invitations is generated according toinstructions contained in computer-readable logic of the presentinvention to list recent invitations, a subject, date of invitation, andstatus of the invitation. Status symbols such as Accepted, Rejected,Accepted and Reciprocated, Pending, and others can be used to indicatethe status of an invitation. Other fields can be included in theinvitation table, such as the user-selected context, and the like.Further, computer-readable logic can also be included in the presentinvention to generate a sent-invitation table to tabulate recentinvitations extended by the user, and the status of those invitations.

Upon receiving notice of the invitation's existence via email, forexample, computer-readable logic included as part of the system presentsthe invitee with a hyperlink to a response page, where the invitee ispresented with a plurality of optional responses as shown in FIG. 5. Inthe embodiment shown in FIG. 5, the invitee can accept and send areciprocal invitation, accept without sending a reciprocal invitation,and decline the invitation to join the user's personal communicationnetwork.

If the invitee accepts the invitation, a direct communication link isestablished between the user and the invitee, meaning that the inviteehas joined the user's personal communication network, and that theinvitee is now a first-degree contact or is separated from the user byonly one degree of separation. The user's first-degree contacts arestored electronically in a computer accessible memory provided to aserver, for example. Additionally, the invitee has become a member ofthe user's personal communication network and is thereby linked to allof the nodes in the user's personal communication network. It will beappreciated that the nodes in the user's personal communication networkwill be two or more degrees of separation away from the invitee once theinvitee has accepted an invitation from the user. As a member of theuser's personal communication network, the invitee can search orestablish communications with other members of the user's personalcommunication network via the invitee's link through the user.

The fact that the invitee has accepted the invitation to become afirst-degree contact of the user does not necessarily mean that the userhas become a first-degree contact of the invitee. Whether the userbecomes a first-degree contact of the invitee is a consequence of thedirection of the communication link. For example, in the scenario wherethe invitee accepts the user's original invitation and declines to offera reciprocal invitation to the user, the communication link is said tobe unidirectional from the user to the invitee. In this case, theinvitee is a first-degree contact of the user, but the user is not afirst-degree contact of the invitee.

If the user sent an invitation to the invitee, the invitee accepted theinvitation and extended a reciprocal invitation to the user, the usercan accept the reciprocal invitation in much the same way as the inviteehas to become a first-degree contact of the user. The user's acceptancecan be automatic if the user selected the automatic acceptance optionshown in FIG. 4, or the user can manually accept such a reciprocalinvitation. In this scenario, the communication link between the userand the invitee is a bidirectional communication link, meaning that theuser and the invitee are first-degree contacts of each other and consultwith each other in the specified contexts.

Finally, the invitee can decline the invitation from the user, therebynot becoming a first-degree contact of the user. If this occurs,computer-readable logic will generate and send a response indicating theinvitee's desire to decline the invitation. The invitee's response canoptionally include a personal statement issued by the invitee indicatinghis/her reasons for declining the invitation.

The process of inviting and receiving invitations from others to bringpersons or users into the systems entire inventory of personalcommunication networks (the entire inventory being described as a globalnetwork) and establish first-degree contacts is a continuous process. Asa nonlimiting example, invitations to join a personal-communicationnetwork will typically be extended to registered physicians as thoseextending the invitations encounter medical-related issues with whichthe invited physicians have experience. Once a physician has accepted aninvitation to join a personal communication network, the physician cansearch for members of that personal communication network to engage withrespect to a particular matter, as well as for members of other personalcommunication networks that are linked by a chain of communication.

A chain of communication is a communication path that has anuninterrupted path from one node to another in a user-specified context.As shown in FIG. 8, example (I) is a chain of communication between NodeA and Node C that includes Node B therebetween. This means that Node Acan establish communication with Node C using Node B as an introduction,or by merely explaining to Node C that Node A is a contact of Node B.And Node A can form a preliminary opinion about Node C based on whatNode A already knows about Node B. If Node B is a very astute individualthat exercises great discretion in establishing first degree contacts,Node A can assume that Node C is a reasonably-reliable contact.

Further, example (II) is a four-node chain of communication thatincludes Nodes A, B, C and D. Node A can establish communication withNode D through Nodes B and C. This does not require Node A tocommunicate first with Node B, followed by Node B communicating withNode C, and finally Node C communicating with Node D. Instead, Node Acan communicate directly with any node, including Node D, in an attemptto establish a dialogue with Node D. As mentioned above, Node A can getan idea of the character of Node C by examining the nodes that standbetween Node A and Node D.

Referring again to example (II), Nodes B, C and D are all considered tobe in the personal communication network of Node A. Generally, each ofNodes A, B, C and D are considered to be in each other's personalcommunication network. In fact, any node that a user can establishcommunications with via an uninterrupted chain of communication isconsidered to be in the personal communication network of the base node.Note that for a node to be considered within the personal communicationnetwork of the user, communications can be established with any numberof degrees separating the node from the user. However, the user canelect to display only those possible contacts that are within apredetermined degree of separation from the user. Other criteria canalso be used to limit the number of nodes that are displayed in responseto a search using the system of the present invention.

In one embodiment, each time a first-degree contact is added to theuser's contact list, this increases the user's status as an opinionleader. The system includes computer-readable logic that identifies oneor more opinion leaders based on at least the number of first-degreecontacts each user has. Additionally, the computer-readable language canidentify one or more opinion leaders within a specific subset of theentire network. For instance, the system of the present invention canidentify one or more opinion leaders in the field of pharmacology, orone or more opinion leaders in the field of medical education, or one ormore opinion leaders in a geographic area, and so on.

The system can optionally generate a listing of the one or more opinionleaders and cause the listing of opinion leaders to be displayed by thecomputer terminal with which the user accessed the system of the presentinvention. Computer-readable logic can include instructions controllingthe identification and display of the opinion leaders.

The system of the present invention can optionally includecomputer-readable logic for identifying one or more innovators. Anynumber of factors such as those recited above can be considered andassigned a value to be evaluated by an algorithm included in thecomputer-readable logic.

FIG. 6 is an illustrative arrangement of a Search Screen generated by aCPU under the instruction of computer-readable logic of the presentinvention. The user can input one or more key words relating tosymptoms, medications, therapeutic agents, ailments, diseases, viralinfections, physicians, hospitals, insurance providers, and any otherterm into a key-word field, and optionally narrow the scope of thesearch to a particular subcategory of the entire network. For example,the scope of the search can be narrowed by specifying an insuranceprovider, the number of degrees of separation between the user andanother registered physician that could possess knowledge of interest tothe user, registered physicians within a predetermined geographicdistance from the location of a user or other person, a specificcontext, and any other specification that will narrow the scope of thesearch for the key words input by the user.

Selecting the Go button instructs the system to initiate the searchbased on the user-specified key words entered into the key-word field.Computer-readable logic instructs the search to retrieve all possibleresults that satisfy the key words. These results are then filtered toremove any results that do not comply with the specifications, orotherwise fall within the desired subcategory selected by the user.

FIG. 7 is an illustrative Search-Results screen generated according toinstructions included in computer-readable logic of the presentinvention and displayed by the computer terminal. The search resultsinclude the names of physicians in the user's personal communicationnetwork that satisfy the search criteria input into the Search Screen.The results in FIG. 7 are tabulated with the first-degree, or othermost-closely-related contacts that satisfy the query listed at the topof the table. The physicians that satisfy the query can possessknowledge or experience with respect to a certain ailment, practicewithin a predetermined geographic distance from a user-specifiedlocation, or otherwise be relevant with respect to the key words andother criteria used to perform the search.

As shown in FIG. 7, first-degree contacts listed in the first columndirectly next to the user's profile are physicians who have beenpersonally invited by the user to join the user's personal communicationnetwork. The second-degree, or other second most-closely-relatedcontacts are listed in the second column, but starting in rows directlybeneath rows that list the most-closely-related contacts. For example,in FIG. 7, the first-degree contacts returned by the search are listedin the first column, and in the first two rows. In rows 3 and 4, thesecond-degree contacts are listed in the second column, each of saidsecond-degree contacts being separated from the user's profile by afirst-degree contact.

The first-degree contact that separates each second-degree contact fromthe user in FIG. 7 is a node in the chain of communication that extendsfrom the user to the second-degree contact. Obviously, the user truststhe first degree contact, otherwise the user would not have extended aninvitation to the first-degree contact to join the user's personalcommunication network. The user can make a preliminary determinationabout the trustworthiness of the second-degree contact by consideringthe first-degree contact (Node B) between the user (Node A) and thesecond-degree contact (Node C). For example, if the first-degree contactis a physician in a teaching hospital who is primarily concerned withacademic research of a particular disease, the second-degree contactknown by the first-degree contact is likely to have a similarbackground. In another example, the first-degree contact may have becomeless reputable in light of recent accusations of falsifying experimentaldata. If the second-degree contact was at one time a research partnerwith the first-degree contact, the user can exercise caution inconsulting with the second-degree contact. Regardless of therelationship with the first-degree contact, the user can often obtain aninitial impression on the second-degree contact based on his familiaritywith the first-degree contact.

Referring once again to FIG. 7, the computer-readable logic of thepresent invention can also cause n^(th) degree contacts to be displayedin an arrangement similar to that above for first and second-degreecontacts. Third-degree contacts shown in FIG. 7 are listed in the thirdcolumn from the user and start on row 5. Again, the user can gain apreliminary impression of the trustworthiness of the third-degreecontact by considering the trustworthiness of the first andsecond-degree contacts between the third-degree contact and the user.

Those personal-communication-network members who satisfy the searchcriteria, key words, etc. . . . entered with the Search Screen can beidentified as those search results that are highlighted. Additionally,one or more of the search results can be selected with a cursor, border,or other visual indicia, and profile information of the selected searchresult can be shown in a profile window displayed by a display deviceoperatively coupled to the computer terminal by computer-readable logic.The user, once making a preliminary determination about thetrustworthiness of the selected search result, can communicate with theselected search result via contact information provided in the profilewindow. Additionally, contact options are presented in the profilewindow to provide the user with alternate methods of contacting theselected search result. Examples of contact options include Message,allowing the user to send a message to the selected contact with amessenger feature of the present invention; Chat, which allows the userand the selected contact to enter a chat room provided by the presentinvention; and other contact options.

By way of example, authorized users are permitted to enter a statisticalenvironment where they can obtain statistical information aboutphysicians that are members of at least one personal communicationnetwork. Access to the statistical environment can be restricted by alogin or other security feature that would allow authorized users intothe statistical environment while minimizing the ability of unauthorizedusers to gain access to the statistical environment. Similar to theSearch Screen, the statistical environment will permit the user tospecify the statistics the user wishes to observe. For example, the usercan select to observe at least one of the opinion leaders, theinnovators, and any other class of physicians. Further, the opinionleaders, innovators, and other classes of physicians displayed accordingto the present invention can be limited to particular contexts,geographic regions, and other specifications similar to those recitedabove to limit the search results displayed on the Search-ResultsScreen.

Although the system and method are described herein with reference tothe medical field, it is understood that the system and method of thepresent invention can be employed in any field. Further, the searchresults can be arranged in any manner that permits observation of thechain of communication between the user and members of the user'spersonal communication network returned by the search.

One aspect of this invention is directed to searching for a member of asearcher's social network or personal communication network wherein thatmember has information on a topic. A search for information within one'spersonal communication network can involve using one or more searchstrategies. A nonlimiting example of two search strategies are: abroadcast search and/or a directed search. As to the former, a broadcastsearch involves a person contacting everyone she knows on a first namebasis when seeking out information and, in turn, each of these peoplewould contact everyone they know asking the same question untiltheoretically everyone in the network has been contacted or theperson(s) who possess the information are found. On the other hand, adirected search involves selecting and contacting who, among one'sdirect contacts, is most likely to possess the relevant information orknows of someone within his or her personal communication network whodoes. This person would then be contacted and, if he or she did notpossess the relevant information, would determine who is most likelyamong his or her direct contacts to possess the relevant information. Inthis case, a probability estimate and search strategy is based on thefollowing criteria:

1) degree of knowledge/awareness and trust of who knows what (i.e.,local information) among direct contacts which is acquired throughvarious interactions over time.

It may be the case that other direct contacts possess relevantinformation, or know of someone who does, but it is more efficient if asearcher approaches a direct contact based on some relevant parameterwhich correlates with the information being sought. For example, it ismore efficient to search through a direct contact's personalcommunication network if that contact is a lawyer and the question hasto do with the law, than it is to search through a direct contact'snetwork if that contact is a carpenter. That is, a lawyer is more likelyto know other lawyers; whereas, a carpenter may know a lawyer(s), but itis more likely they know and have strong connections to othercarpenters. Of course, if the search was relevant to building furniture,it would be more efficient to search through the carpenter's personalcommunication network. Using such “local” information is an effectivestrategy to conducting a targeted search. The present invention providesa method and system by which a searcher can manually select certainparameters to effectively search his or her personal communicationnetwork to identify the shortest path between the searcher and theperson(s) who possess the relevant information wherein the mainparameter is based on “local information” (i.e., personal knowledge ofdirect contacts).

A directed search can be described as a search strategy that can be usedto search a collection of linked databases. A directed search isdistinct from a broadcast search because in most cases, less than all ofthe available searchable databases will be searched in the directedsearch, and the sequence of databases that are searched in a directedsearch will have a logical basis. In one embodiment, an anchor databaseor anchor node is selected by the searcher, and the anchor database oranchor node is commonly a first-degree contact. The anchor database isthen searched (e.g., using computer-readable logic) for the sought-aftersearch term(s). After the anchor database or anchor node has beensearched, additional databases or nodes are selected to be searchedbased upon their similarity to the anchor database or anchor node.

An anchor database is a database that is used in a directed search toaid in guiding or directing the search to meaningful databasesthroughout a collectively-linked database network. In one embodiment, ananchor database is the first database to be searched in a directedsearch. An anchor database also serves as the basis for selectingadditional databases to be searched throughout the course of a directedsearch. In one embodiment, an anchor database is used in a similaritycorrelation to make a relative determination of which directly-linkeddatabase is most like the anchor database. And a database that isdirectly linked to the anchor database and which is also most like theanchor database, relative to the other directly-linked databases, isthen searched for the sought-after data. For illustration, the databasethat is directly linked to the anchor database and that has beenidentified by a similarity correlation as being most like the anchordatabase will be called the “second-searched database” (thefirst-searched database being the anchor database). The “second-searcheddatabase” is then searched for the sought-after data. The directedsearch can then proceed from the “second-searched database” to a“third-searched database.” The “third-searched database” is a databasethat is directly linked to the “second-searched database” (but it is notthe anchor database) and identified by a similarity correlation as beingmost like the anchor database relative to other databases that aredirectly linked to the “second-searched database.” A directed search canproceed on in this manner through a “third-searched database,” a“fourth-searched database,” a “fifth-searched database,” and so forththrough an “nth-searched database.” There is no limit on the number ofdatabases that can be searched using a directed search method.

Any database can act as an anchor database. In one embodiment, a node ina social network map can be an anchor database. In another embodiment,an internet or intranet website can act as an anchor database.

In another search embodiment, a directed-search strategy is conductedthrough the “second-searched database,” “third-searched database,” and“fourth-searched database” and then from that database, the searchstrategy stops being a directed search strategy and becomes a broadcastsearch of all databases that are directly and then indirectly linked tothe database at which the directed search strategy ended. This is anexample of a combination of directed and broadcast search strategies,and this combination of search strategies is within the scope of theinvention.

In a social-network search embodiment, a directed search strategy canalso be combined with historical search data. In such an embodiment, thehistorical data relates to determining who among a social-network node'sfirst-degree contacts the node historically identified as an anchor inconducting a search on a particular topic. Stated differently, if a nodeconducting a search identified one of their first-degree contacts as ananchor regarding a search relating to “cars,” the historical data willreflect that that node made that first-degree contact anchor selectionwhen the topic was “cars”. And a social-network search strategy maycombine a directed search strategy with historical data in order toguide a search throughout a social network. In such a social-networksearch strategy, a directed search (as has been described above) of thesocial network may be performed and when the directed search reaches anode that has historical data relating to the subject search topic, thecurrent search may be redirected based upon the historical anchorselection that the node previously made on the same or similar searchtopic. In other words, in a search embodiment, historical data may beused to override a directed-search similarity-correlation calculation inmaking a determination as to which database/node is to be searched next.

In yet another embodiment, the historical data can be used to initiate asecond search in addition to the existing directed search. As an exampleof such an embodiment, a directed search of a social network isconducted until it reaches a node with historical data relating toanchor-database/anchor-node selection on the current search topic. Uponreaching that node, two separate searches may spring from that node. Oneof those searches may be a continuation of the initial directed searchthat proceeds to follow a search path dictated by a similaritycorrelation determination. The second search will be initiated/directedto a node based upon historical data and not based upon a similaritycorrelation calculation. So at any point during the course of a directedsearch, a second search may be initiated based upon historical data.

In yet another embodiment, any combination of search strategies; i.e., adirected search strategy, a broadcast search strategy, and ahistorical-data search strategy; may be employed in performing a searchof a collectively-linked databases or a social network.

In another embodiment, this invention provides for simultaneouslyinitiating two or more directed searches of at least one collection oflinked databases. More specifically, two or more directed searches canbe initiated simultaneously, wherein a first search is performed on afirst collection of linked databases and a second search is performed ona second collection of linked databases.

Another embodiment of this invention is directed to initiating adirected search from a single search field. This is performed byentering into the search field: both a directed-search search term and aterm that identifies an anchor database. A differentiator is used withinthe field to differentiate the directed-search search term from the termthat identifies the anchor database. The differentiator is also used toindicate which of the two terms is the directed-search search term andwhich of the two terms is the term that identifies an anchor database.FIG. 23 provides an illustration of this embodiment, wherein thedirected-search search term is Fishing; the term that identifies theanchor database is “Bill Dance”; and parenthesis are used as the visualindicator. In an embodiment, the differentiator can be a visual oraudible.

Computer-readable logic can be used to perform any of this invention'ssearch methods.

A similarity correlation is an algorithm or mathematical function usedto determine the degree of similarity between two databases. Anyalgorithm or mathematical function can be used to perform this function.As a nonlimiting example, a useful algorithm or mathematical functionwould simply count the number of data entries in common (i.e., shared)between the two databases. The degree of similarity could then bedescribed on a percentage basis by a function having the form:

$\left( \frac{\;{{{Number}\mspace{14mu}{of}\mspace{14mu}{Data}\mspace{14mu}{Entries}\mspace{14mu}{in}\mspace{14mu}{Common}}\text{}{{Between}\mspace{14mu} a\mspace{14mu}{First}\mspace{14mu}{and}\mspace{14mu}{Second}\mspace{14mu}{Database}}}}{\mspace{11mu}{{{Total}\mspace{14mu}{Number}\mspace{14mu}{of}\mspace{14mu}{Data}\mspace{14mu}{Entries}}\text{}{{Possessed}\mspace{14mu}{by}\mspace{14mu}{the}\mspace{14mu}{First}\mspace{14mu}{Database}}}} \right) \times 100\%$Other forms of relative comparison can also be employed.

Linked databases are databases that are connected to each other in somemanner. As a nonlimiting example of linked databases, wherein people arecharacterized as databases, a social network represents a group ofpeople or databases that are linked to one another through the peoplethat they know. In other words, social networks illustrate how peopleare linked to the people that they know directly (first-degree contacts)as well as to the people that they know indirectly through theirfriends. As another example of linked databases, electronic models ofactual social networks will often assign attributes to each electronicsocial-network node, and those attributes may be directed to anode/person's profession, hobbies, geographic location, or otherdescriptive characteristic. The collection of attributes that areassigned to a particular social network node make up a single databaseof data that can be used to describe the subject social-network node.And each individual electronic social-network node has such adescriptive database assigned to it. So an electronic model of a socialnetwork will commonly have a plurality of descriptive databases that arelinked to each other, through electronic links or electronicconnections, in an arrangement that is representative of the actualsocial network. The databases are linked by electronic links orelectronic connections represent an embodiment of linked databaseswithin the scope of the present invention. Other embodiments whereindatabases are linked electronically or in some other way are also withinthe scope of this invention.

In general, at least one embodiment of this invention is directed to amethod or system for searching databases. Further, this invention isdirected to a method or system for searching one or more databases inorder to identify at least one database that has data on a topic. In oneembodiment, the search method or system is applied to a plurality ofdatabases that are collectively linked together in a highly-branchedarchitecture. A nonlimiting two-dimensional illustrative example of ahighly-branched architecture of a collection of linked databases isprovided:

wherein D is a database; and

wherein “-” is a link between two databases

In one embodiment, social networks and personal communication networksserve as nonlimiting examples of collections of linked databases havinghighly-branched architectures upon which the inventive search method orsystem can be applied.

In one embodiment, the search method or system can be applied to acollection of linked databases that have an architecture wherein atleast a portion of the architecture can be described by the expression:

wherein D_(x) is a seed database;

wherein each D represents a database;

wherein each “-” represents a link between two databases; and

wherein “a” is an integer greater than or equal to 1.

As a nonlimiting example, an architecture of a collectively-linkeddatabase that falls within the scope of the expression:

wherein “a” is 4,

is presented:

In another embodiment, the search method or system can be applied to acollection of databases that have at least a portion of theirarchitecture that can be described by the expression:

wherein D_(x) is a seed database;

wherein D represents a database;

wherein each “-” represents a link between two databases;

wherein a is an integer greater than or equal to 1;

wherein b is an integer greater than or equal to 0; and

wherein the value of each b is independently selected.

As nonlimiting examples, two architectures of collective databases thatfall within the scope of the expression:

wherein “a” is 4 and wherein each “b” is 1,

are presented:

Still further, in another embodiment, the search method or system can beapplied to a collection of databases that have at least a portion oftheir architecture that can be described by the expression:

wherein D_(x) is a seed database;

wherein each D represents a database;

wherein each “-” represents a link between two databases;

wherein each a is an integer greater than or equal to one;

wherein each b is an integer greater than or equal to 0;

wherein each c is an integer greater than or equal to 0; and

wherein each b and c is independently selected.

As a nonlimiting example, an architecture of collective databases thatfalls within the scope of the expression:

wherein “a,” “b,” and “c” are as described above,

is presented:

As mentioned above, one embodiment for performing a directed searchinvolves searching for information within a plurality of databases thatare collectively linked together in a highly-branched architecture. Inone particular embodiment, a directed search is used to search a socialnetwork or personal communication network. Further, a directed search ofsuch a collection of individual databases involves searching less thanall of the individual databases in the collection. Instead, the searchfor the information is channeled or directed to the individual databasesthat are most likely to contain the sought-after data or information, orhave access to a database that does. And as a result, a directed searchof such a collection of databases typically involves searching only aportion of the individual databases in the entire collection.

All of the databases described above are within the scope of beingsearched using this invention's search methods.

Another embodiment of this invention is directed to establishing asocial-network path from a search initiator to a person that isidentified in a website. Stated differently, if a search initiatorconducting an internet or intranet website search wants to know of atleast one social-network path that connects them to a specific personthat has been named or identified in a specific website, then thisembodiment provides for establishing at least one social-network pathfrom the search initiator to the person that is identified in thewebsite. In a particular embodiment, the website that names oridentifies the person is listed among the search initiator's websitesearch results.

In order to establish a social-network path from a search initiator to aperson that is either named or identified in a website,computer-readable logic is used to match the person identified in thewebsite with a representative node in an existing social-network map. Inother words, the computer-readable logic searches one or more existingsocial-network maps for a social-network node that represents the personidentified in the website.

When the computer-readable logic is searching for a match, the sequencein which the computer-readable logic searches for the match is notintended as a limitation on the present invention. In other words, in afirst type of search sequence, the computer-readable logic searches fora match by basing the search on the identity in the website andsubsequently searches for a node in an existing social-network mapwherein the node represents the identity in the website. Once thecomputer-readable logic locates such a representative node, the computerreadable logic forms a match between the two. Alternatively, in a secondtype of search sequence, the computer-readable logic determines therepresentative identity of a node in an existing social-network map andsubsequently searches for an identity or name match in the targetwebsite. In yet another embodiment, the computer-readable logic performsthe match by employing both types of search sequences simultaneously. Instill another embodiment, the computer-readable logic can perform acombination of the two types of search sequences in order to match theperson identified in a website with a node in a social network map. Anyknown computer-readable logic or search engine can be used in thisinvention to perform a search function that matches either 1) asocial-network node to an identity in a website or 2) an identity in awebsite to a social-network node.

There is no limitation on the types of social-network maps that can beused in performing a match between a social-network node and a personthat is either named or identified in a website. As mentioned above, anembodiment of this invention provides for performing thesocial-network-node/website-identity match using a social-network mapthat has a node representing the search initiator. In one embodiment,this invention's computer-readable logic performs a match by searchingrepresentative nodes in a social-network map that has been constructedusing an invitation-and-acceptance method as described above.

For ease of explanation, a social-network node that represents theidentity in the website will herein be identified as thewebsite-identity node. Furthermore, a social-network node thatrepresents the search initiator will herein be identified as thesearch-initiator node. Once the computer-readable logic has successfullyperformed a match between a social-network node and a person identifiedin a website, and thereby determined that the website identity is a nodein a social network, additional computer-readable logic is used toselect a social-network path between the search-initiator node and thewebsite-identity node. In establishing a social-network path between thesearch-initiator node and the website-identity node, thesearch-initiator node and the website-identity node are preferably partof the same social-network map.

Where the search-initiator node and the website-identity node are partof the same social-network map, the map may provide for any number ofsocial-network paths between the search-initiator node and thewebsite-identity node. And the actual number of social-network pathsbetween the search-initiator node and the website-identity node is in noway a limitation on the present invention. In one embodiment, thecomputer-readable logic actually establishes a social-network path byselecting an existing social-network path from among those available inthe social-network map, wherein the selected path connects thesearch-initiator node to the social-network node. The computer-readablelogic can select any social-network path from the social-network map, aslong as the selected path connects the search-initiator node to thewebsite-identity node. In one embodiment, the computer-readable logicselects an existing path from the social-network map, wherein relativeto all of the paths from the search-initiator node to thewebsite-identity node, the selected path has the fewest number ofintervening nodes between the search-initiator node and thewebsite-identity node.

In one embodiment, a path from the search-initiator node to thewebsite-identity node can be displayed in combination with the websitelisted as a search result. In another embodiment, the website searchresult is the product of an internet search or an intranet search.

As a nonlimiting example, FIG. 9 provides an embodiment of an interfacethat will act as a bridge or gateway allowing the user/search initiatorto search multiple databases and various types of databases eitherindividually or simultaneously. Such databases may include, but are notlimited to, social search networks and social search engines,traditional search engines, individual websites or webpages (such aspopular sites like Amazon.com or sites that the user frequently visits),online databases such as Medline, individuals, groups, institutions,governments, and the like. The interface will allow for generalbroadcast searches as well as anchored, directed searches, and the userwill also be able to type particular web addresses into the browser. Theuser will also have the option to edit the lists that appear in theirpersonal manifestations of this interface. For example, if user Xfrequently visits webmed.com to search for information, the interfacewill allow (and possibly even prompt) the user to add webmd.com to itslist of anchors. Below are some visual examples of this interface andexamples of the utility of such interface.

FIG. 10 provides a nonlimiting embodiment of a social-search-engineresults display. More specifically, FIG. 10 provides a clear delineationof one or more social-network paths connecting the user (searchinitiator) to social-network nodes matching the search initiator'ssearch criteria.

FIG. 11 provides an embodiment for viewing/displaying a social networkpath from a user/search initiator to a social-network member (Dr. AnnaMeadows). This path could be provided (1) on the current web page, (2)on the traditional results page or toolbar, or (3) it could open a newwindow with social search engine results displayed, where the user islogged in as the user and “Anna Meadows” is the query term.

As a nonlimiting example, FIG. 12 provides a search embodiment wherein asearch initiator wants to locate Frank Ecock within her interpersonalnetwork. She suspects that Mike Markus may know Frank or know of someonewho does. Therefore, she anchors her search with a person, “MikeMarkus,” by clearing the boxes and checking only the box next to Mike'sname. Note, searching through a person may require that the user/searchinitiator uncheck all the boxes next to the other databases, too, byselecting “clear all.”

FIG. 13 provides an embodiment of a search result display based upon thesearch described in FIG. 12.

As a nonlimiting example, FIG. 14 provides a search embodiment wherein asearch initiator wants to find Frank Ecock within her interpersonalnetwork, and she suspects that Mike Markus may know Frank or know ofsomeone who does. However, she also wants to search for relevantinformation regarding Frank on the World Wide Web using the googlesearch engine. In this case, Heather performs a search using twoanchors, Mike Markus and google.com. To do so, she anchors her searchwith a person, “Mike Markus,” by clearing the boxes and checking onlythe box next to Mike's name, and by clearing the boxes in the otherdatabase table (by selecting “clear all”) and checking the box next towww.google.com.

FIG. 15 provides an embodiment of a search result display based upon thesearch described in FIG. 14. In this embodiment, the first anchoredsearch (via Mike) yields the results presented in the top half of the“split screen;” the path from Heather (the user) to Frank Ecock (thequery). The second anchored search (via Google) yields the resultspresented in the bottom half of the screen.

As a nonlimiting example, FIG. 16 provides a search embodiment wherein asearch initiator wants to locate information regarding cancer within herinterpersonal network. She suspects that Brian Smith may haveinformation on the topic cancer or know someone who does. Therefore, sheanchors her search with a person, “Brian Smith,” by clearing the boxesand checking only the box next to Brian's name.

FIG. 17 provides an embodiment of a search result display based upon thesearch described in FIG. 16. In these results, Brian has information oncancer, and all of the other individuals listed in the results table (1)have information regarding cancer, and (2) are connected to Heather (theuser) via her first degree colleague Brian Smith. (we can tell this bynoting that Brian is listed repeatedly in the first column).

As a nonlimiting example, FIG. 18 provides a search embodiment wherein asearch initiator wants to find information regarding “cancer” within herinterpersonal network, and she suspects that Brian Smith may haveinformation on the topic cancer or know someone who does. However, shealso wants to search for relevant information regarding cancer on theWorld Wide Web using the google search engine. In this case, Heatherperforms a search using two anchors, Brian Smith and google.com. To doso, she anchors her search with a person, “Brian Smith,” by clearing theboxes and checking only the box next to Brian's name, and by clearingthe boxes in the website table (by selecting “clear all”) and checkingthe box next to www.google.com

FIG. 19 provides an embodiment of a search result display based upon thesearch described in FIG. 18. In this case, the first anchored search(via Brian) yields the results presented in the top half of the “splitscreen;” the path from Heather (the user) to people in her interpersonalnetwork that have information regarding cancer (the query). The secondanchored search (via Google) yields the results presented in the bottomhalf of the screen. These results are interactive. For example, ifHeather (the user) clicks on a person's name in the top half of thescreen, in this example she has clicked on Brian Smith, then the bottomhalf of the screen presents Google results in which the person's name(e.g. Brian) and the original search query (i.e. cancer) becomes the newsearch query.

FIG. 20 provides yet another embodiment of a search results displaybased upon the search described in FIG. 18. In this case, the resultslook similar to traditional google search results with one exception—thelist line of each paragraph/the last part of the description for eachindividual result, indicates the path from the user (i.e. Heather) tothe individual with the queried information that is listed, cited, etc.in that particular result. In this example, the search was anchored viaBrian Smith, so Brian is always the first link in the paths of theseresults.

FIG. 21 provides an embodiment of a search result display that could beemployed in a system in which a web crawler locates all websites and webpages relevant to (e.g. written by or including information about) allnew and current social-network nodes/users or if a social network andtraditional network were to merge or otherwise “join forces” andintegrate databases. In this case, the results could be a formattingembodiment of the social search engine results page such that, when asearch initiator types in “cancer” instead of receiving a list ofphysicians' names and paths connecting the search initiator to thoseindividuals, the search initiator is provided with a list of websitesand web pages identified by the social search engine's web crawler asincluding information about network members and users. These resultswould be organized in manner that could be a hybrid form of traditionalsearch results pages—including the URL (uniform resource locator), nameof the site or page, description, etc.—as well as components of thesocial search engine results page—personal profiles and paths linkingthe user to the author, publisher, or person affiliated with the websiteor web page.

Another embodiment of the invention is directed to constructing one ormore social-network maps that serve as social-network models. Inparticular, an embodiment of this invention provides a method or systemfor substituting a portion of a first social-network map with at least aportion of a second social-network map. More specifically, an embodimentof the invention is directed to substituting a portion of a firstsocial-network map with at least a portion of a second social-networkmap, wherein the portion of the first social-network map is asocial-network path and the portion of the second social-network map isa social-network path. Computer-readable logic can be used to performany of the social-network map or social-network path substitutions. Inorder to substitute a first social-network path with at least a portionof a second social-network path, the first social-network path at leastin part has the form:

and the portion of the second social-network path has the form:

wherein each D represents a node;

wherein D_(A) represents a first node;

wherein D_(B) represents a second node;

wherein each D_(X) represents an intervening node between D_(A) andD_(B);

wherein “y” is an integer greater than or equal to zero;

wherein “z” is an integer greater than or equal to zero; and

wherein each “-” represents a link between two nodes.

As nonlimiting examples, two exemplary social-network paths that fallwithin the scope of the general form:

is a first social-network path having four intervening nodes:D_(A)-D_(X)-D_(X)-D_(X)-D_(X)-D_(B)and a second social-network path having five intervening nodes:D_(A)-D_(X)-D_(X)-D_(X)-D_(X)-D_(X)-D_(B)Other nonlimiting examples of two exemplary social-network paths thatfall within the scope of the general form:

is a third social-network path having one intervening node:D_(A)-D_(X)-D_(B)and a fourth social-network path having two intervening nodes:D_(A)-D_(X)-D_(X)-D_(B)

A nonlimiting visual example of one of this invention's embodiments forsubstituting a first social-network path with at least a portion of asecond social-network path is provided below.

A first social-network path from D₁ to D₇:D₁-D₂-D₃-D₄-D₅-D₆-D₇

wherein the portion of the first social-network path represented by:

is substituted with a second social-network path:

thereby producing a new social-network path:D₁-D₂-D₈-D₉-D₆-D₇In the above nonlimiting example of substituting a first social-networkpath with at least a portion of a second social-network path, the newsocial-network path has a different intervening path than theintervening path in the first social-network path.

Another embodiment of this invention is directed to copying oraltogether removing a portion of a social-network map and substitutingthat portion back into a different section of the same social-networkmap. This same-social-network-map substitution embodiment is performedin a similar manner as the above-described substitution method forsubstituting a portion of a first map into a second map, with theexception that in this embodiment the portion of the map that is copiedor altogether removed—is substituted back into a different location ofthe same social-network map from which it was taken.

To further define the use of computer readable logic in a substitutionembodiment of this invention, computer-readable logic can be used todefine the portions of a first social-network map that are to besubstituted into a different portion of the first social-network map orthat are to be substituted into a second social-network map. In order todefine the social-network portions that are to be substituted orsubstituted into, an embodiment provides that the computer-readablelogic identifies an existing path between two nodes, and then locatesalternate paths between the two nodes from among paths in existingsocial-network maps.

There is no limit on the different types of substitutions that can bemade into a social-network map or social-network path. In oneembodiment, the substitution replaces or removes at least one node inthe intervening-node portion of a social-network path. In anotherembodiment, the substitution adds one or more additional nodes to theintervening-node portion of a social-network path. In still anotherembodiment of the invention, the substitution replaces one or moreintervening nodes, removes one or more intervening nodes, adds at leastone or more intervening nodes, rearranges one or more intervening nodes,or a combination thereof to the intervening-node portion of asocial-network path.

Another embodiment of this invention is directed to constructing asocial-network map by grafting a section of a first social-network maponto at least one node in a second social-network map. Still anotherembodiment of this invention is directed to copying or removing asection of a first network map and grafting it onto a different portionof the first social-network map. Grafting occurs when at least a portionof a social-network map is copied or removed from one section of thesocial-network map and directly linked to a node in another section ofthe social-network map. Grafting also occurs when a portion of a firstsocial-network map is copied or removed from a section of the firstsocial-network map and directly linked to a node in a secondsocial-network map.

Below is a nonlimiting visual example of a portion of a firstsocial-network map that is grafted onto a second social-network map. Theportion of the first social-network map represented by:

wherein each “D₁” is a database from the first social-network map; and

wherein each

is a link between the databases,

the portion of the second social-network map represented by:

wherein each “D₂” is a database from the second social-network map; and

wherein each

is a link between the databases,

and the portion of the first social-network map grafted onto the portionof the second social-network map represented by:

wherein “D₁”, “D₂”, and

are as described above; and

wherein

represents the point of grafting.

Computer-readable logic can be used to perform the grafting of one ormore collections of linked databases onto a node or another collectionof linked databases.

In one grafting embodiment, social networks and personal communicationnetworks serve as nonlimiting examples of collections of linkeddatabases having highly-branched architectures upon which the method orsystem for grafting can be applied.

In one embodiment, the grafting method or system can be applied tografting a collection of linked databases to another collection oflinked databases wherein at least a portion of each of thelinked-database architectures can be described by the expression:

wherein D_(x) is a seed database;

wherein each D represents a database;

wherein each “-” represents a link between two databases; and

wherein “a” is an integer greater than or equal to 1.

As a nonlimiting example, an architecture of a collection of linkeddatabases that falls within the scope of the expression:

wherein “a” is 4,

is presented:

In another embodiment, the grafting method or system can be applied tografting a collection of linked databases to another collection oflinked databases wherein at least a portion of each of thelinked-database architectures can be described by the expression:

wherein D_(x) is a seed database;

wherein D represents a database;

wherein each “-” represents a link between two databases;

wherein a is an integer greater than or equal to 1;

wherein b is an integer greater than or equal to 0; and

wherein the value of each b is independently selected.

As nonlimiting examples, two architectures of collectively-linkeddatabases that fall within the scope of the expression:

wherein “a” is 4 and wherein each “b” is 1,

are presented:

Still further, in another embodiment, the grafting method or system canbe applied to grafting a collection of linked databases to anothercollection of linked databases wherein at least a portion of each of thelinked-database architectures can be described by the expression:

wherein D_(x) is a seed database;

wherein each D represents a database;

wherein each “-” represents a link between two databases;

wherein each a is an integer greater than or equal to one;

wherein each b is an integer greater than or equal to 0;

wherein each c is an integer greater than or equal to 0; and

wherein each b and c is independently selected.

As a nonlimiting example, an architecture of collectively-linkeddatabases that falls within the scope of the expression:

wherein “a,” “b,” and “c” are as described above,

is presented:

Another embodiment of this invention is directed to visually qualifyinga link between two nodes in a social-network map. Visually qualifying alink can be performed in a number of different ways, and this inventionis not limited to any specific type of visual qualification. Nonlimitingexamples of visual qualifiers that can be used to visually qualify alink between two linked databases or two nodes in a social-network mapare: a colored line, a number on or in close proximity to a line, a lineof varying thickness, a dashed line, a dotted line, or a combinationthereof. More specifically, a visual link qualification can be used toqualify any link in a collection of linked databases, and in oneembodiment, the collection of linked databases is made up eitherentirely or at least in part by social-network nodes. Visual qualifierscan be used to indicate the type of link between two nodes. Asnonlimiting examples, a visual qualifier for a link between nodes can beused to describe the quantity of different categories of data that areexchanged between the first database and the second database, the numberof communications that are exchanged between the first database and thesecond database, or the length of time the first database has beenlinked to the second database.

In one embodiment for using visual qualifiers to describe a link betweentwo linked databases, the linked databases are linked websites. Inanother embodiment for using visual qualifiers to describe a linkbetween two linked databases, the linked databases are linked socialnetwork nodes.

A nonlimiting example of a method for displaying a portion of acollection of linked databases, and specifically a link between twodatabases, uses color to visually qualify the link. Specifically, a linkbetween two databases has the form:

-   -   wherein “D₁” is a first database,    -   wherein “D₂” is a second database,    -   wherein “-” represents a link between the first database and the        second database,    -   wherein “c” represents a color designation of the “-” link        between the first database and the second database, and    -   wherein the color designation of the “-” link qualifies the link        as any of two or more possible link qualifications.

An additional nonlimiting example of a method for displaying a portionof a collection of linked databases, and specifically a link between twodatabases, uses a number to visually qualify the link. Specifically, alink between two databases has the form:

-   -   wherein “D₁” is a first database,    -   wherein “D₂” is a second database,    -   wherein “-” represents a link between the first database and the        second database, and    -   wherein “n” is a number that qualifies the link between the        first database and the second database.

An embodiment of this invention is directed to recording directed-searchdata. Specifically, an embodiment of the invention is directed to makinga record, electronic or other, that a particular search term and anchordatabase were used in combination to perform a directed search of acollection of limited databases. A directed search can be performedusing any of the embodiments described herein. Furthermore, making arecord that a search term was used in combination with a particularanchor database can be applied to a directed search of any collection oflinked databases. The collection of linked databases can be a collectionof linked websites on an internet, a collection of linked websites on anintranet system, a collection of linked nodes having the form of asocial-network map, a collection of linked databases that is the productof an invitation and acceptance method, or a collection of linkeddatabases wherein each linked databases is independently selected froman internet website, an intranet website, and a social-network node.

Another embodiment of this invention is directed to using the record ofa search term and anchor database that have been used in combination toqualify a database as an opinion leader, as a database that is mostlikely to have information on a topic relative to other databases in acollection of linked databases, as a database that is more likely thannot to have information on a topic relative to other databases in acollection of linked databases, as a database that is most likely to bedirectly linked to another database having information on a searchtopic, or as a database that is more likely than not to be directlylinked to a database having information on a topic. Yet anotherembodiment of this invention is directed to visually displaying thedatabase qualification to a user or administrator after the record hasbeen used to qualify the database.

Still another embodiment of this invention is directed to an inferentialnetwork and related systems and methods. An inferential network is adistinct network that is constructed as a result of one or more directedsearches of one or more collections of linked databases. Stateddifferently, an inferential network is a network that is separate fromthe one or more collection of linked databases that are subject to adirected search. Further, an inferential network is a network that isconstructed based upon the inferences that one or more search initiatorsmake in selecting an anchor database for a directed search.

To further define an inferential network and its construction, themechanics of a directed search of a collection of linked databases mustbe understood. As mentioned above, a directed search is initiated by asearch initiator using a keyword search in combination with an anchordatabase that the search initiator has selected as being most likely topossess information on the search topic, as being most likely to bedirectly linked to another database having information on the searchtopic, or a combination thereof. In selecting an anchor database, thesearch initiator is making an inference about what information theanchor database possesses, about the databases that the search anchor islikely to be directly linked to, or a combination thereof. Further, thesearch initiator is drawing an inference about which database is mostlikely to have information on a topic, about the databases that are asingle degree of separation from the anchor database, or a combinationthereof. In summary, the search initiator is drawing an inference on ananchor database and databases that are a single degree of separationaway from the anchor database.

As a nonlimiting example, if a search initiator is conducting a directedsearch of a collection of linked databases and the search topic is“cancer,” then the search initiator will select an anchor database bydrawing an inference on which database in a collection or collections oflinked databases is most likely to possess information on the searchtopic “cancer,” by drawing an inference on which database is most likelyto be directly linked to another database having information on“cancer,” or a combination thereof. And it is the search initiator'sinference in selecting an anchor database that provides the basis forthe inferential link between the inferential-network search-initiatornode and the inferential-network anchor-database node.

An inferential network is a network that is based upon the inferencesthat one or more directed-search search initiators have made about theone or more anchor databases that they have selected in conducting theirdirected searches. Further, an inferential network is made up of one ormore inferential links between inferential-network nodes. In oneembodiment, an inferential network is made up entirely ofinferential-network nodes and inferential links, wherein the inferentiallink or links represent the inferences that one or more databases havemade about another database or databases.

As a nonlimiting example, an inferential link is or can be createdbetween a first inferential-network node and a secondinferential-network node wherein the first inferential-network noderepresents a directed-search search initiator that has conducted adirected search using a search term in combination with an anchordatabase and wherein the second inferential-network node represents theanchor database used in the directed search. The directionality of aninferential link between a first inferential-network node and a secondinferential-network node is from the first inferential-network node thatrepresents a directed-search search initiator to the secondinferential-network node that represents the anchor database used in thesearch initiator's directed search. In one embodiment, an inferentiallink is created when a search initiator initiates a directed search. Inanother embodiment, an inferential link is created after a searchinitiator initiates a directed search. In still another embodiment, theinferential link is created as a function of search data,directed-search search data, broadcast-search search data, or acombination thereof.

In another embodiment, an inferential link can be created when a searchinitiator selects or electronically clicks on one of the searchinititator's search results. Because the search initiator is making aninference about which of the search results is most likely to possessinformation on the search term or search topic, an inferential link canbe created from an inferential-network node representing the searchinitiator to an inferential-network node representing the selectedsearch result. As nonlimiting examples, the search results or selectedsearch result can be a website, a social-network node, aninferential-network node, or any electronic database or documentavailable on the internet or on an intranet system.

In still another embodiment of this invention, an inferential link canbe created outside the setting of a directed search that requires afirst-degree contact or first-degree database to be selected as ananchor database. For example, consider the illustrative displaygenerated by the computer processor according to computer-readable logicshown in FIG. 24. In FIG. 24, the search initiator is optionallyprovided with a field in which he can specify an anchor database otherthan one of his first-degree contacts in his personal communicationnetwork, and other than the websites or other predeterminedanchor-database options. For example, the search initiator can login toa website outside of the personal-communication network setting thatwill allow the search initiator to conduct the equivalent of a directedsearch. Just as before, the search initiator can specify a search stringin a search field, but instead of selecting an anchor database from afinite number of available options, the search initiator can specify anydesired anchor database in an “anchor database” field. In this manner,the search initiator is provided with the freedom to select any anchordatabase without being constrained to network members who have accepteda formal invitation or other predetermined options.

In a nonlimiting example of creating an inferential link when a searchinitiator selects or electronically clicks on one of the searchinititator's search results; if a search initiator performs a broadcastsearch on a social network, the search results can be displayed and thesearch initiator can select any of the returned members of the socialnetwork that may possess information of the search topic. Selection ofmembers of the social network displayed in the search results can becarried out by clicking on a hyperlink identifying the members, or byany other suitable method. When one or more members of the socialnetwork are selected from the search results, an inferential link can becreated between a first inferential-network node representing the searchinitiator that performed the selection and a second inferential-networknode representing the selected social-network member. In a specificembodiment, an inferential link is be created between a firstinferential-network node representing the search initiator thatperformed the selection and a second inferential-network noderepresenting the selected social-network member.

In creating an inferential link, there is no limitation on thecollections of linked databases that can be used in performing adirected search. As nonlimiting examples, an inferential link can becreated from a directed search wherein the anchor database is a websitethat is selected from among a collection of linked websites on theinternet, wherein the anchor database is a website that is selected fromamong a collection of linked websites on an intranet system, wherein theanchor database is a node selected from among a collection of linkednodes in a social-network map, or a combination thereof.

In an embodiment, an inferential-network search-initiator node and aninferential-network anchor-database node can be created simultaneouslywith the initiation of a directed search. In another embodiment, aninferential-network search-initiator node and an inferential-networkanchor-database node can be created following the performance of adirected search. In a specific embodiment, an inferential-networksearch-initiator node and an inferential-network anchor-database nodeare created before or at the same time as inferential link is createdbetween them. In any of the above embodiments for creating aninferential-network node, an inferential-network search-initiator nodeor an inferential-network anchor-database node can be createdindependently. In other words, if an inferential-network noderepresenting a search initiator exists, but an inferential-network noderepresenting an anchor database does not yet exist, then an embodimentprovides for creating only an inferential-network node representing theanchor database. Likewise, if an inferential-network node representingan anchor database exists, but an inferential-network node representinga search initiator does not yet exist, then an embodiment provides forcreating only an inferential-network node representing the searchinitiator.

In another embodiment for creating an inferential-network node, theinferential-network node is created as a function of search data,directed-search search data, broadcast-search search data, or acombination thereof.

In an embodiment, inferential links and inferential-network nodes can beused to create a visual map of an inferential network. Aninferential-network map is a visual display that represents therelationships or links in an inferential network.

In an embodiment, an inferential link between and firstinferential-network node and a second inferential-network node can bequalified with a subject-matter based qualification. As mentioned above,an inferential link from an inferential-network search-initiator node toinferential-network anchor-database node is based upon the inferencethat the search initiator has made in selecting the anchor database inconducting a directed search. In one embodiment, qualifying aninferential link is based at least in part on the search term or searchtopic used to conduct the directed search. As a nonlimiting example, ifa search initiator were to conduct a directed search of a social networkmap that was the product of an invitation-and-acceptance process, andthe search initiator (Dr. Markus) designated “Dr. Smith” or asocial-network node representing Dr. Smith as an anchor database for asearch on “cancer,” then an inferential link would be created from aninferential-network node representing Dr. Markus to aninferential-network node representing Dr. Smith. And the inferentiallink would be labeled as a “cancer” inferential network link from aninferential-network node representing Dr. Markus to aninferential-network node representing Dr. Smith.

An additional embodiment provides for qualifying an inferential linkwith more than one subject-matter based qualification. In thisembodiment, the directed-search search term, which was used in thedirected search that gave rise to the inferential link, is associatedwith one or more related terms or phrases that are used to createadditional subject-matter based labels or qualifications for theinferential link. So, in this embodiment, an inferential link can bequalified with multiple subject-matter based qualifications, whereineach qualification is based at least in part on the search initiator'soriginal directed-search search term. A nonlimiting embodiment forproviding additional subject-matter based qualifications for aninferential link uses a library of predetermined terms that have beendesignated in advance as being related to one another. And if adirected-search search initiator uses a search term that is in thelibrary of predetermined terms, then an inferential link arising out ofthat directed search will have multiple subject-matter basedqualifications as defined in the library of predetermined terms. In oneembodiment, an inferential link has one subject-matter basedqualification. In another embodiment, an inferential link has two ormore subject-matter based qualifications. In still another embodiment,an inferential link has three or more subject-matter basedqualifications. There is no limit on the number of subject matter-basedqualifications that an inferential link can have.

An additional embodiment of this invention is directed to increasing thestrength of an inferential link between a first inferential-network nodeand a second inferential-network node. The strength of an inferentiallink increases as a function of the number of directed searches that adirected-search search initiator performs wherein the search initiatoruses the same anchor database in combination with the same search termor search topic. In other words, an inferential link increases instrength as a directed-search search initiator performs repeateddirected searches using the same anchor database in combination with thesame or similar search terms. In one embodiment, an inferential linkincreases directly in proportion with the number of directed searchesthat a search initiator performs by using the same anchor database incombination with the same or similar search terms. There is nolimitation on the types of mathematical functions that can be used todetermine the strength of an inferential link based upon the number ofdirected searches that a search initiator performs by using the sameanchor database in combination with the same or similar search terms.Additionally, there are no limitations on the functions that can beperformed on inferential-network data in order to arrive at the strengthof an inferential link.

Another embodiment of this invention is directed to decreasing thestrength of an inferential link as a function of time. Stateddifferently, once an inferential link is created between a firstinferential-network node and a second inferential-network node, anembodiment of this invention provides for decreasing the strength ofthat inferential link over time. A further embodiment of the inventionprovides for decreasing the strength of an inferential network to suchan extent that the inferential link will cease to exist given enoughtime. There is no limitation on the rate at which an inferential linkwill decrease in strength. Additionally, there are no limitations on thefunctions that can be performed on inferential-network data in order toarrive at a rate for decreasing the strength of inferential link.

FIG. 22 represents illustrative relationships betweeninferential-network nodes A-K within an inferential network according toan embodiment of the present invention. The inferential-network nodesA-K, can represent any entity capable of possessing informationregarding one or more topics and include: people, websites, books,documents, microfiche, motion pictures, video or audio broadcasts,drawings, illustrations, and so on. The spatial arrangement of the nodesin the figure is merely intended to illustrate interaction between thenodes, and is not considered to limit the scope of the presentinvention. The inferential-network node located at the start of a lineextending between two inferential-network nodes, which represents aninferential link, will be referred to as an inferential-networksearch-initiator node for that particular inferential link. Likewise,the inferential-network node adjacent to the arrow at the terminal endof each link between two inferential-network nodes will be considered aninferential-network anchor-database node as specified by thecorresponding search initiator. It is apparent from FIG. 22 that aninferential-network node can represent both a search initiator and ananchor database. Further, the term or phrase intersecting eachinferential link indicates the context or subject of the informationsought by the search initiator in initiating the search. Still further,the relative strength of an inferential link can be assessed from thethickness of the line (a visual indicator).

An inferential network such as that shown in FIG. 22 can be created anddeveloped over time by the system and method of the present invention.The inferential network will evolve as search initiators conductdirected searches or the equivalent of directed searches over time toreflect the perceived possession of knowledge amongst members of theinferential network pertaining to a variety of topics. In the generalsense, an inferential link is created as a result of a directed searchinitiated by a search initiator. In conducting the directed search, thesearch initiator specifies a search string that can be a subject,keyword, phrase, person, a combination thereof, or any other item thatthe search initiator seeks information about, along with an anchordatabase that the search initiator believes possesses the informationsought. An anchor database can refer to any person, website,publication, database, social-network member, or any other potentialsource of information that the search initiator believes has theinformation he or she is searching for.

An additional embodiment of this invention is directed to qualifying aninferential-network node. Nonlimiting examples of useful qualificationsinclude 1) qualifying the inferential-network node as a node thatrepresents a database that is most likely to have information on asearch topic relative to other databases represented by nodes in aninferential network, and 2) qualifying the node as a node thatrepresents a database that is more likely than not to have informationon a search topic relative to other databases represented by nodes in aninferential network. There is no limitation on the types ofqualifications that can be used to qualify an inferential-network node.Additionally, there are no limitations on the functions that can beperformed on inferential-network data in order to arrive at aqualification for an inferential-network node.

In one embodiment, an inferential-network node is qualified at least inpart based upon on the strength of inferential links to theinferential-network node. As mentioned above, the directionality of aninferential link between a first inferential-network node and a secondinferential-network node is from the first inferential-network node thatrepresents a directed-search search initiator to the secondinferential-network node that represents the anchor database used in thesearch initiator's directed search. So in one embodiment, an inferentiallink is an indicator of which database (anchor database) thedirected-search search initiator believes is most likely to possessinformation on a search topic. In an additional embodiment, the strengthof the inferential link reflects the strength of the inference that thedirected-search search initiator is drawing on a specific database or aspecific node representing a database. For example, if a searchinitiator designates a specific database as an anchor database in adirected search, then the strength of the inference represented by thatsingle directed search is not as strong as if that same search initiatorperformed ten directed searches that used the same anchor database incombination with the same or a similar search term or topic. As thestrength of the inferential link increases so does the likelihood thatthe anchor database actually possesses information on thedirected-search search topic.

Therefore, for example, if eight directed-search search initiatorsperform directed searches independent of each other, but use the sameanchor database in combination with the same or a similar search term,then the likelihood that the anchor database actually possessesinformation on the search topic increases because there will be eightinferential links to the inferential-network node that represents theanchor database. Furthermore the subject-matter qualifications of theeight links will be the same. So qualifying the inferential-network nodeas a node that represents a database that is most likely to haveinformation on a search topic relative to other databases represented bynodes in an inferential network can be a function of both the strengthand number of inferential links leading to the inferential-network nodethat represents the anchor database. Stated differently, aninferential-network node can be qualified as a function of the strengthof one or more inferential links in one or more inferential networks.

An additional embodiment of this invention is directed to establishingan inferential-network path from a first inferential-network node to asecond inferential-network node. In one embodiment, aninferential-network path from a first inferential-network node to asecond inferential-network node is established by selecting an existinginferential-network path from among paths in an inferential network. Inan additional embodiment for establishing an inferential-network pathfrom a first inferential-network node to a second inferential-networknode, the first inferential-network node and the secondinferential-network node are part of the same inferential network.

Where the first inferential-network node and the secondinferential-network node are part of the same inferential network, theinferential network may provide for any number of inferential-networkpaths between the first inferential-network node and the secondinferential-network node. And the actual number of inferential-networkpaths between the first inferential-network node and the secondinferential-network node is in no way a limitation on the presentinvention. In one embodiment, computer-readable logic actuallyestablishes an inferential-network path by selecting an existinginferential-network path from among those available in the inferentialnetwork, wherein the selected path connects the firstinferential-network node to the second inferential-network node. Thecomputer-readable logic can select any inferential-network path from theinferential network, as long as the selected path connects the firstinferential-network node to the second inferential-network node. In oneembodiment, the computer-readable logic selects an existing path fromthe inferential network, wherein relative to all of the paths from thefirst inferential-network node to the second inferential-network node,the selected path has the fewest number of intervening nodes between thefirst inferential-network node to the second inferential-network node.

In an additional embodiment, the computer-readable logic selects aninferential-network path from the first inferential-network node to thesecond inferential-network node, wherein the selected path has the leastnumber of intervening nodes between the first inferential-network nodeand the second inferential-network node relative to otherinferential-network paths from the first inferential-network node to thesecond inferential-network node.

In still another embodiment, the computer-readable logic selects aninferential-network path from the first inferential-network node to thesecond inferential-network node, wherein the sum of the strengths of theinferential links in the selected path is the greatest relative to otherinferential-network paths having the least number of intervening nodesbetween the first inferential-network node and the secondinferential-network node.

In yet another embodiment, the computer-readable logic selects aninferential-network path from the first inferential-network node to thesecond inferential-network node, wherein the first inferential-networknode represents an inferential-network search initiator and the secondinferential-network node represents a database that is most likely tohave information on a search topic relative to other databasesrepresented by nodes in the inferential network. In another embodiment,the second inferential-network node has been qualified as a noderepresenting a database that is most likely to have information on asearch topic relative to other databases represented by nodes in aninferential network. In yet another embodiment, the secondinferential-network node has been qualified as a node representing adatabase that is more likely than not to have information on a searchtopic relative to other databases represented by nodes in an inferentialnetwork.

In yet another embodiment, this invention is directed to providing ahistorical list of directed-search search terms or directed-searchsearch topics that were anchored to an anchor database.Computer-readable logic can be used to perform this embodiment byrecording the directed-search search terms or directed-search searchtopics that have been anchored to a particular database during adirected search. A further embodiment provides for usingcomputer-readable logic to make the directed-search search termsavailable in a visual display or other known methods for displaying orproviding information. Any method for recording data can be used torecord the directed-search search data. One embodiment for initiatingthe display of the directed-search search terms or directed-searchsearch topics that were anchored to an anchor database uses anelectronic command. As nonlimiting examples, electronically pressing anelectronically-executable command button associated with ananchor-database node or an inferential-network anchor-database node cancause the historical list of directed-search search terms ordirected-search search topics that were anchored to the anchor databaseto be displayed.

Another embodiment of the invention is directed to constructing one ormore inferential networks. In particular, an embodiment of thisinvention provides a method or system for substituting a portion of afirst inferential network with at least a portion of a secondinferential network. More specifically, an embodiment of the inventionis directed to substituting a portion of a first inferential networkwith at least a portion of a second inferential network, wherein theportion of the first inferential network is an inferential-network pathand the portion of the second inferential network is aninferential-network path. Computer-readable logic can be used to performany of the inferential network or inferential-network pathsubstitutions. In order to substitute a first inferential-network pathwith at least a portion of a second inferential-network path, the firstinferential-network path at least in part has the form:

and the portion of the second inferential-network path has the form:

wherein each D represents an inferential-network node;

wherein D_(A) represents a first inferential-network node;

wherein D_(B) represents a second inferential-network node;

wherein each D_(X) represents an intervening inferential-network nodebetween D_(A) and D_(B);

wherein “y” is an integer greater than or equal to zero;

wherein “z” is an integer greater than or equal to zero; and

wherein each “-” represents a link between two inferential-networknodes.

As nonlimiting examples, two exemplary inferential-network paths thatfall within the scope of the general form:

is a first inferential-network path having four interveninginferential-network nodes:D_(A)-D_(X)-D_(X)-D_(X)-D_(X)-D_(B)and a second inferential-network path having five interveninginferential-network nodes:D_(A)-D_(X)-D_(X)-D_(X)-D_(X)-D_(X)-D_(B)Other nonlimiting examples of two exemplary inferential-network pathsthat fall within the scope of the general form:

is a third inferential-network path having one interveninginferential-network node:D_(A)-D_(X)-D_(B)and a fourth inferential-network path having two interveninginferential-network nodes:D_(A)-D_(X)-D_(X)-D_(B)

A nonlimiting visual example of one of this invention's embodiments forsubstituting a first inferential-network path with at least a portion ofa second inferential-network path is provided below.

A first inferential-network path from D₁ to D₇:D₁-D₂-D₃-D₄-D₅-D₆-D₇

wherein the portion of the first inferential-network path representedby:

is substituted with a second inferential-network path:

thereby producing a new inferential-network path:D₁-D₂-D₈-D₉-D₆-D₇In the above nonlimiting example of substituting a firstinferential-network path with at least a portion of a secondinferential-network path, the new social-network path has a differentintervening path than the intervening path in the firstinferential-network path.

Another embodiment of this invention is directed to copying oraltogether removing a portion of an inferential network and substitutingthat portion back into a different section of the same inferentialnetwork. This same-inferential-network substitution embodiment isperformed in a similar manner as the above-described substitution methodfor substituting a portion of a first inferential network into a secondinferential network, with the exception that in this embodiment theportion of the network that is copied or altogether removed—issubstituted back into a different location of the same inferentialnetwork from which it was taken.

To further define the use of computer readable logic in a substitutionembodiment of this invention, computer-readable logic can be used todefine the portions of a first inferential network that are to besubstituted into a different portion of the first inferential network orthat are to be substituted into a second inferential network. In orderto define the inferential-network portions that are to be substituted orsubstituted into, an embodiment provides that the computer-readablelogic identifies an existing path between two inferential-network nodes,and then locates alternate paths between the two inferential-networknodes from among paths in existing inferential networks.

There is no limit on the different types of substitutions that can bemade into an inferential network or inferential-network path. In oneembodiment, the substitution replaces or removes at least oneinferential-network node in the intervening-node portion of aninferential-network path. In another embodiment, the substitution addsone or more additional inferential-network nodes to the intervening-nodeportion of an inferential-network path. In still another embodiment ofthe invention, the substitution replaces one or more interveninginferential-network nodes, removes one or more interveninginferential-network nodes, adds at least one or more interveninginferential-network nodes, rearranges one or more interveninginferential-network nodes, or a combination thereof to theintervening-node portion of an inferential-network path.

Another embodiment of this invention is directed to constructing aninferential network by grafting a section of a first inferential networkonto at least one node in a second inferential-network. Still anotherembodiment of this invention is directed to copying or removing asection of a first inferential network and grafting it onto a differentportion of the first inferential network. Grafting occurs when at leasta portion of an inferential network is copied or removed from onesection of the inferential network and directly linked to a node inanother section of the inferential network. Grafting also occurs when aportion of a first inferential network is copied or removed from asection of the first inferential network and directly linked to a nodein a second inferential network.

Below is a nonlimiting visual example of a portion of a firstinferential network that is grafted onto a second inferential network.The portion of the first inferential network represented by:

wherein each “D₁” is an inferential-network node from the firstinferential network; and

wherein each

is an inferential link between the inferential-network nodes,

the portion of the second inferential network represented by:

wherein each “D₂” is an inferential-network node from the secondinferential network; and

wherein each

is an inferential-network link between the inferential-network nodes,

and the portion of the first inferential network grafted onto theportion of the second inferential network represented by:

wherein “D₁”, “D₂”, and

are as described above; and

wherein D₁

D₂, represents the point of grafting.

Computer-readable logic can be used to perform the grafting of one ormore collections of linked databases onto a node or another collectionof linked databases.

In one grafting embodiment, inferential networks serve as nonlimitingexamples of collections of linked databases having highly-branchedarchitectures upon which the method or system for grafting can beapplied.

In one embodiment, the grafting method or system can be applied tografting one inferential network to another inferential network whereinat least a portion of each of the inferential-network architectures canbe described by the expression:

wherein D_(x) is a seed inferential-network node;

wherein each D represents an inferential-network node;

wherein each “-” represents an inferential-network link between twoinferential-network nodes; and

wherein “a” is an integer greater than or equal to 1.

As a nonlimiting example, an architecture of an inferential network thatfalls within the scope of the expression:

wherein “a” is 4,

is presented:

In another embodiment, the grafting method or system can be applied tografting one inferential-network to another inferential-network whereinat least a portion of each of the inferential-network architectures canbe described by the expression:

wherein D_(x) is a seed inferential-network node;

wherein D represents an inferential-network node;

wherein each “-” represents an inferential-network link between twoinferential-network nodes;

wherein a is an integer greater than or equal to 1;

wherein b is an integer greater than or equal to 0; and

wherein the value of each b is independently selected.

As nonlimiting examples, two architectures of inferential networks thatfall within the scope of the expression:

wherein “a” is 4 and wherein each “b” is 1,

are presented:

Still further, in another embodiment, the grafting method or system canbe applied to grafting one inferential network to another inferentialnetwork wherein at least a portion of each of the inferential-networkarchitectures can be described by the expression:

wherein D_(x) is a seed inferential-network node;

wherein each D represents an inferential-network node;

wherein each “-” represents an inferential-network link between twoinferential-network nodes;

wherein each a is an integer greater than or equal to one;

wherein each b is an integer greater than or equal to 0;

wherein each c is an integer greater than or equal to 0; and

wherein each b and c is independently selected.

As a nonlimiting example, an architecture of an inferential network thatfalls within the scope of the expression:

wherein “a,” “b,” and “c” are as described above,

is presented:

Yet another embodiment of this invention is directed to simultaneouslydisplaying inferential-network search results in combination withinternet search results, intranet system search results, orsocial-network-map data search results. In one embodiment, the internetor intranet search results are website search results. One embodimentfor accomplishing this simultaneous display of search results usescomputer-readable logic to use a first portion of a visual displayscreen, e.g., a computer monitor, to display inferential-network searchresults and use a second portion of the visual display screen to displayinternet search results, intranet search results, or social-network-mapdata search results. One embodiment for displaying inferential-networksearch results in combination with internet, intranet, orsocial-network-map data search results uses two separate electronicwindows. Specifically, on a visual-display screen a first electronicwindow is used for displaying inferential-network search results, and asecond electronic window is used for displaying internet, intranet, orsocial-network-map data search results. There is no limitation on thepercentages of a screen that can be used to display either theinferential-network search results or the internet, intranet, orsocial-network-map data search results. In one embodiment, at least 50%of the visual display screen is used to display the inferential-networksearch results. In another embodiment, at least 10% of the visualdisplay screen is used to display the inferential-network searchresults. In another embodiment, at least 50% of the visual displayscreen is used to display the internet, intranet, or social-network-mapdata search results. In still another embodiment, at least 10% of thevisual display screen is used to display the internet, intranet, orsocial-network-map data search results.

In one embodiment, the inferential-network search, the internet search,the intranet search, the social-network-map data search, or acombination thereof use the same search term. In yet another embodiment,the inferential-network search, the internet search, the intranetsearch, the social-network-map data search, or a combination thereof areinitiated simultaneously from a single visual-display-screen interfacewith the search initiator.

Another embodiment of this invention is directed to visually qualifyingan inferential link between two inferential-network nodes in aninferential network. Visually qualifying an inferential link can beperformed in a number of different ways, and this invention is not limitto any specific type of visual qualification. Nonlimiting examples ofvisual qualifiers that can be used to visually qualify an inferentiallink between two inferential-network nodes in an inferential-networkare: a colored line, a number on or in close proximity to a line, a lineof varying thickness, a dashed line, a dotted line, or a combinationthereof. More specifically, a visual link qualification can be used toqualify any inferential link in an inferential network, and in oneembodiment, the inferential-network is made up either entirely or atleast in part by inferential-network nodes. Visual qualifiers can beused to indicate the type of inferential link between twoinferential-network nodes. As nonlimiting examples, a visual qualifierfor an inferential link between inferential-network nodes can be used todescribe the strength of the inferential link or the length of time thefirst inferential-network node has been linked to the secondinferential-network node.

In one embodiment for using visual qualifiers to describe a link betweentwo linked databases, the linked databases are linked websites. Inanother embodiment for using visual qualifiers to describe a linkbetween two linked databases, the linked databases are linked socialnetwork nodes.

A nonlimiting example of a method for displaying a portion of aninferential network, and specifically an inferential link between twoinferential-network nodes, uses color to visually qualify the link.Specifically, an inferential link between two inferential-network nodeshas the form:

-   -   wherein “D₁” is a first inferential-network node,    -   wherein “D₂” is a second inferential-network node,        -   wherein “-” represents an inferential link between the first            inferential-network node and the second inferential-network            node,        -   wherein “c” represents a color designation of the “-” link            between the first inferential-network node and the second            inferential-network node, and    -   wherein the color designation of the “-” link qualifies the        inferential link as any of two or more possible link        qualifications.

An additional nonlimiting example of a method for displaying a portionof an inferential network, and specifically an inferential link betweentwo inferential-network nodes, uses a number to visually qualify thelink. Specifically, an inferential link between two inferential-networknodes has the form:

-   -   wherein “D₁” is a first inferential-network node,    -   wherein “D₂” is a second inferential-network node,    -   wherein “-” represents an inferential link between the first        inferential-network node and the second inferential-network        node, and    -   wherein “n” is a number that qualifies the inferential link        between the first inferential-network node and the second        inferential-network node.

This invention also provides for using computer-readable logic thatsearches inferential-network data for multiple terms or phrases byinitiating the search with a single search term. In other words, anembodiment is directed to using a single term or phrase to initiate amulti-term search of inferential-network data. Computer-readable logicinitiates a multi-term search of the inferential-network data by firstidentifying one or more terms or phrases that will be searched inaddition to the single search term or phrase that was entered by a useror searcher. The computer-readable logic does this by associating thesingle search term or phrase with a predetermined set of additionalsearch terms or search phrases that have been pre-selected to besearched in addition to the single search term or phrase. Thecomputer-readable logic then applies both the single search term orphrase and the predetermined set of additional search terms or searchphrases in a search of one or more databases of inferential-networkdata.

Additionally, if a search term or search phrase used in aninferential-network data search does not literally match any terms orphrases in the inferential-network data, the present invention hasprovided computer-readable logic for matching specific conditions,treatments, pharmaceutical drugs, and medical specialties to selectedsearch terms and phrases. Therefore, computer-readable logic will searchfor at least one predetermined search term or phase that has beenassociated with the initial search term or phrase. And although theremay be no literal match to the initial search term, meaningful searchresults can still be generated based upon the social search engine'scomputer-readable logic searching for additional related terms orphrases.

An embodiment of this invention is also directed to using inferentialnetwork data to order search results. Stated differently, search resultscan be ordered as a function of inferential-network data, e.g.,strengths of inferential links or inferential-network nodequalifications. The method by which the search results are obtained isin no way a limitation on the invention, e.g., the search results can beobtained by a broadcast search, a directed search, or any other knownsearch method. In an embodiment, ordering of search results can beaccomplished by first identifying inferential-network nodes thatrepresent each of the search results, and then using theinferential-network data relating to each of the inferential-networknodes to assign an order to the results. As a nonlimiting example, if abroadcast search returns three search results and each of the searchresults is represented by an inferential-network node in an inferentialnetwork, then the three search results could be ordered in descendingorder as a function of the combined strengths of all inferential linksleading to each of the nodes, wherein the links are qualified with thesearch term or search topic. To illustrate this point, if each of theone or more inferential links leading to each of the three nodes all hadthe same strength and were qualified with the search term or searchtopic, then the ordering of search results would be based upon which ofthe three nodes had the greatest number of inferential links leading toit. Alternatively, the search results could be ordered as a function ofone or more inferential-network node qualifications, wherein each of theinferential-network nodes relates to one of the search results.

An inferential network can exist in cyberspace or any other mediumsuitable for collecting, holding, or describing data relating thereto.Further, computer-readable logic can be used to perform any of the aboveembodiments relating to inferential networks.

In light of the foregoing, it should thus be evident that the presentinvention substantially improves the art. While, in accordance with thepatent statutes, only the preferred embodiments of the present inventionhave been described in detail hereinabove, the present invention is notto be limited thereto or thereby. Rather, the scope of the inventionshall include all modifications and variations that fall within thescope of the attached claims.

What is claimed is:
 1. A method for ordering search results using inferential network data, said method comprising: searching a first network of linked nodes for a search term, each of the nodes connected to another one of the nodes by a link, wherein the search begins at a node in the first network specified in the search query; retrieving stored inferential network data describing inferences made about nodes in the first network, the inferences derived from electronic search data collected from previously conducted searches of the first network, the electronic search data including a) search terms used in the previously conducted searches and b) corresponding search results, wherein the inferential network data describes the inferences as a second, inferential network of linked inferential nodes, each of the inferential nodes corresponding to a node of the first network and connected to another one of the inferential nodes by an inferential link, the inferential link including a strength, the strength increasing with the number of previously conducted searches that result in an inference corresponding to the inferential link and decreasing as a function of time, wherein a previously conducted search results in an inference corresponding to the inferential link when a node of the first network associated with the inferential link is designated as an anchor database or a node of the first network associated with the inferential link is designated as an anchor database in a search for an identical or related search term; for each of the results of the search: identifying an inferential node of the inferential network that represents the result; and assigning a weight to the result based on the combined strengths of all inferential links leading to the identified node from other inferential nodes; and weighing the results of the search based on the assigned weights of the results; and displaying the results of the search ordered according to the weighing.
 2. The method of claim 1, wherein inferential network data is selected from the group consisting of search data from searches conducted using an anchor database, broadcast-search data, and a combination of broadcast-search search data and search data from searches conducted using an anchor database.
 3. The method of claim 1, wherein the inferential network nodes are members of a social network.
 4. The method of claim 1, wherein the inferential network nodes are internet or intranet websites.
 5. The method of claim 1, wherein the inferential link is a subject matter based qualification derived from a search term used in a search that included a designated anchor database. 